2.0 Creates a Garli.conf file for up to five partitions Mark Miller Unpublished Phylogeny / Alignment garli_conf_creator garli perl "ls" 0 infile Alignment file (non-interleaved phylip or nexus format) (s) 0 infile scheduler_input scheduler.conf perl "ChargeFactor=1.0\\n" . "nodes=1\\n" . "node_exclusive=0\\n" . "threads_per_process=1\\n" runtime 1 scheduler.conf perl "runhours=0.1\\n" is_partitioned The input is a Nexus file that specifies at least two partitions linkmodels I would like to evaluate all partitions under a single model perl $is_partitioned && !$configure_partitions 2 garli.conf perl "linkmodels =1\\n" 0 configure_partitions I would like to specify model parameters for each partition perl $is_partitioned && !$linkmodels 2 garli.conf perl ($value) ? "linkmodels =0\\n" : "" 0 numparts How many partitions does your data set have? perl $is_partitioned && $configure_partitions Please enter a value between two and 5 for the number of partitions perl $numparts < 2 Sorry, this interface supports configuration for a maximum of 5 partitions. However, you can download and edit the file created here to support as many parititions as you like. Please see the GARLI manual or home page for more information perl $numparts > 5 subsetspecificrates Infer overall rate multipliers for each data partition perl $is_partitioned 2 garli.conf perl "subsetspecificrates = $value\\n" 0 The parameter subsetspecificrates means to infer overall rate multipliers for each data subset. This is equivalent to *prset ratepr=variable* in MrBayes. So, there are 4 possible combinations: linkmodels = 0 subsetspecificrates= 0 meaning different models, branch lengths equal linkmodels = 0 subsetspecificrates= 1 meaning different models, different subset rates linkmodels = 1 subsetspecificrates= 0 meaning single model, one set of branch lengths (equivalent to non-partitioned analysis) linkmodels = 1 subsetspecificrates= 1 meaning single model, different subset rates (like site-specific rates model in PAUP*) infile_return Input infile garli_conf Input parameters garli.conf general_section garli.conf 1 perl "[general]\\n" partition_header1 garli.conf 5 perl $configure_partitions perl "\n\n[model1]\\n" partition_header2 garli.conf 7 perl $configure_partitions perl "\n\n[model2]\\n" partition_header3 garli.conf 9 perl $configure_partitions && $numparts > 2 perl "\n\n[model3]\\n" partition_header4 garli.conf 11 perl $configure_partitions && $numparts > 3 perl "\n\n[model4]\\n" partition_header5 garli.conf 13 perl $configure_partitions && $numparts > 4 perl "\n\n[model5]\\n" partition_header6 garli.conf 15 perl $configure_partitions && $numparts > 5 perl "\n\n[model6]\\n" partition_header7 garli.conf 17 perl $configure_partitions && $numparts > 6 perl "\n\n[model7]\\n" partition_header8 garli.conf 19 perl $configure_partitions && $numparts > 7 perl "\n\n[model8]\\n" partition_header9 garli.conf 21 perl $configure_partitions && $numparts > 8 perl "\n\n[model9]\\n" partition_header10 garli.conf 23 perl $configure_partitions && $numparts > 9 perl "\n\n[model10]\\n" master_section garli.conf 91 perl "\n\n[master]\\n" datafname garli.conf 2 perl "datafname = infile\\n" 2 ofprefix garli.conf 2 perl "ofprefix = garli_run\\n" availablememory garli.conf 2 perl "availablememory = 2000\\n" model Model Parameters (For Unpartitioned Data, or Applied to All Partitions) datatype_value The type of data (datatype) perl !$configure_partitions nucleotide nucleotide nucleotide aminoacid amino acid codon-aminoacid codon-aminoacid codon codon nucleotide "datatype = nucleotide\\n" aminoacid "datatype = aminoacid\\n" codon-aminoacid "datatype = codon-aminoacid\\n" codon "datatype = codon\\n" garli.conf 2 The codon-aminoacid datatype means that the data will be supplied as a nucleotide alignment, but will be internally translated and analyzed using an amino acid model. The codon and codon-aminoacid datatypes require nucleotide sequence that is aligned in the correct reading frame. In other words, all gaps in the alignment should be a multiple of 3 in length, and the alignment should start at the first position of a codon. If the alignment has extra columns at the start, middle or end, they should be removed or excluded with a Nexus exset (see the FAQ for an example of exset usage). The correct geneticcode must also be set. geneticcode_value Select the Genetic Code (geneticcode) perl !$configure_partitions && ($datatype_value eq "codon" || $datatype_value eq "codon-aminoacid") perl "geneticcode = $value\\n" standard Standard vertmito Vertebrate Mitochondria invertmito Invertebrate Mitochondria standard garli.conf 2 The codon-aminoacid datatype means that the data will be supplied as a nucleotide alignment, but will be internally translated and analyzed using an amino acid model. The codon and codon-aminoacid datatypes require nucleotide sequence that is aligned in the correct reading frame. In other words, all gaps in the alignment should be a multiple of 3 in length, and the alignment should start at the first position of a codon. If the alignment has extra columns at the start, middle or end, they should be removed or excluded with a Nexus exset (see the FAQ for an example of exset usage). The correct geneticcode must also be set. model_nucleotide Nucleotide Model JC (Jukes-Cantor model): Rate Matrix = 1 rate, Base Frequencies = equal K2P (Kimura 2-Parameter model): Rate Matrix = 2 rate, Base Frequencies = equal F81 (Felsenstein 1981 model): Rate Matrix = 1 rate, Base Frequencies = estimate HKY (Hasegawa, Kishino and Yano model): Rate Matrix = 2 rate, Base Frequencies = estimate GTR (General Time-Reversible model): Rate Matrix = 6 rate, Base Frequencies = estimate d_ratematrix garli.conf Rate Matrix (ratematrix) perl !$configure_partitions && $datatype_value eq "nucleotide" 1rate All Rates Equal (1rate) 2rate HKY (2rate) 6rate General time-reversible (6 rate) fixed fixed rate custom_string User Specified 1rate "ratematrix = $value\\n" 2rate "ratematrix = $value\\n" 6rate "ratematrix = $value\\n" fixed "ratematrix = $value\\n" custom_string "ratematrix = ($ACsubrates $AGsubrates $ATsubrates $CGsubrates $CTsubrates $GTsubrates)\\n" 6rate garli.conf 2 New in version 0.96, parameters for any submodel of the GTR model may now be estimated. The format for specifying this is very similar to that used in the rclass setting of PAUP*. Within parentheses, six letters are specified, with spaces between them. The six letters represent the rates of substitution between the six pairs of nucleotides, with the order being A-C, A-G, A-T, C-G, C-T and G-T. Letters within the parentheses that are the same mean that a single parameter is shared by multiple nucleotide pairs. For example, ratematrix = (a b a a b a) would specify the HKY 2-rate model (equivalent to ratematrix = 2rate). This entry, ratematrix = (a b c c b a) would specify 3 estimated rates of substitution, with one rate shared by A-C and G-T substitutions, another rate shared by A-G and C-T substitutions, and the final rate shared by A-T and C-G substitutions. ACsubrates User specified AC substitution rates (custom ratematrix) perl !$configure_partitions && $datatype_value eq "nucleotide" && $d_ratematrix eq "custom_string" perl "" AGsubrates User specified AG substitution rates (custom ratematrix) perl !$configure_partitions && $datatype_value eq "nucleotide" && $d_ratematrix eq "custom_string" perl "" ATsubrates User specified AT substitution rates (custom ratematrix) perl !$configure_partitions && $datatype_value eq "nucleotide" && $d_ratematrix eq "custom_string" perl "" CGsubrates User specified CG substitution rates (custom ratematrix) perl !$configure_partitions && $datatype_value eq "nucleotide" && $d_ratematrix eq "custom_string" perl "" CTsubrates User specified CT subsitution rates (custom ratematrix) perl !$configure_partitions && $datatype_value eq "nucleotide" && $d_ratematrix eq "custom_string" perl "" GTsubrates User specified GT substitution rates (custom ratematrix) perl !$configure_partitions && $datatype_value eq "nucleotide" && $d_ratematrix eq "custom_string" perl "" d_statefrequencies garli.conf Base Frequencies (statefrequencies) perl !$configure_partitions && $datatype_value eq "nucleotide" perl "statefrequencies = $value\\n" equal equal empirical empirical estimate estimate fixed fixed estimate garli.conf 2 d_invariantsites garli.conf Proportion of invariant sites (invariantsites) perl !$configure_partitions && $datatype_value eq "nucleotide" perl "invariantsites = $value\\n" none none estimate estimate estimate 2 garli.conf Specifies whether a parameter representing the proportion of sites that are unable to change (i.e. have a substitution rate of zero) will be included. This is typically referred to as invariant sites, but would better be termed invariable sites. d_ratehetmodel garli.conf The model of rate heterogeneity (ratehetmodel) perl !$configure_partitions && $datatype_value eq "nucleotide" perl ($d_ratehetmodel eq "none") ? "numratecats = 1\\nratehetmodel = $value\\n" : "numratecats = $d_numratecats\\nratehetmodel = $value\\n" none Equal Rates For All Sites (none) gamma Gamma Distribution (gamma) gamma garli.conf 2 The model of rate heterogeneity assumed. gammafixed requires that the alpha shape parameter is provided, and a setting of gamma estimates it. d_numratecats Number of rate categories (numratecats) perl !$configure_partitions && $datatype_value eq "nucleotide" && $d_ratehetmodel eq "gamma" perl "numratecats=$value\\n" 4 :Number of rate categories: must be an integer between 1 and 20 perl $d_numratecats < 2 || $d_numratecats > 20 garli.conf 2 The number of categories of variable rates (not including the invariant site class if it is being used). Must be set to 1 if ratehetmodel is set to none. Note that runtimes and memory usage scale linearly with this setting. model_protein Protein Model dayhoff Dayhoff, Schwartz and Orcutt. 1978 jones Jones, Taylor and Thornton (JTT), 1992 WAG Whelan and Goldman, 2001 mtREV Adachi and Hasegawa, 1996 mtmam Yang, Nielsen and Hasegawa. 1998 p_ratematrix garli.conf 2 Protein Rate Matrix (ratematrix) perl !$configure_partitions && ($datatype_value eq "aminoacid" || $datatype_value eq "codon-aminoacid") perl "ratematrix = $value\\n" wag poisson Poisson jones Jones dayhoff Dayhoff wag WAG mtmam mtMAM mtrev mtREV You should use the matrix that gives the best likelihood, and could use a program like PROTTEST (very much like MODELTEST, but for amino acid models) to determine which fits best for your data. Poisson assumes a single rate of substitution between all amino acid pairs, and is a very poor model. p_statefrequencies garli.conf 2 Amino Acid Frequencies (statefequencies) perl !$configure_partitions && ($datatype_value eq "aminoacid" || $datatype_value eq "codon-aminoacid") perl "statefrequencies = $value\\n" equal equal empirical empirical (+F) estimate estimate fixed fixed jones Jones dayhoff Dayhoff wag WAG mtmam mtMAM mtrev mtREV empirical Specifies how the equilibrium state frequencies of the 20 amino acids are treated. The empirical option fixes the frequencies at their observed proportions (when describing a model this is often termed +F). p_invariantsites garli.conf 2 Proportion of invariable sites (invariantsites) perl !$configure_partitions && ($datatype_value eq "aminoacid" || $datatype_value eq "codon-aminoacid") perl "invariantsites = $value\\n" none none estimate estimate estimate Specifies whether a parameter representing the proportion of sites that are unable to change (i.e. have a substitution rate of zero) will be included. This is typically referred to as invariant sites, but would better be termed invariable sites. p_ratehetmodel garli.conf 2 Model of rate heterogeneity (ratehetmodel) perl !$configure_partitions && ($datatype_value eq "aminoacid" || $datatype_value eq "codon-aminoacid") perl ($p_ratehetmodel eq "none") ? "numratecats = 1\\nratehetmodel = $value\\n" : "numratecats = $p_numratecats\\nratehetmodel = $value\\n" none Equal Rates For All Sites (none) gamma Gamma Distribution (gamma) gamma The model of rate heterogeneity assumed. gammafixed requires that the alpha shape parameter is provided, and a setting of gamma estimates it. p_numratecats garli.conf 2 Number of rate categories (numratecats; set at no more than 8) perl !$configure_partitions && ($datatype_value eq "aminoacid" || $datatype_value eq "codon-aminoacid") && $p_ratehetmodel eq "gamma" perl "numratecats=$value\\n" 4 Number of rate categories: must be an integer between 1 and 20 perl $p_numratecats < 2 || $p_numratecats > 20 The number of categories of variable rates (not including the invariant site class if it is being used). Must be set to 1 if ratehetmodel is set to none. Note that runtimes and memory usage scale linearly with this setting. model_codon Codon Model The codon models are built with three components: (1) parameters describing the process of individual nucleotide substitutions, (2) equilibrium codon frequencies, and (3) parameters describing the relative rate of nonsynonymous to synonymous substitutions. The nucleotide substitution parameters within the codon models are exactly the same as those possible with standard nucleotide models in GARLI, and are specified with the ratematrix configuration entry. Thus, they can be of the 2rate variety (inferring different rates for transitions and transversions, K2P or HKY-like), the 6rate variety (inferring different rates for all nucleotide pairs, GTR-like) or any other sub-model of GTR. The options for codon frequencies are specified with the statefrequencies configuration entry. The options are to use equal frequencies (not a good option), the frequencies observed in your dataset (termed empirical in GARLI), or the codon frequencies implied by the F1x4 or F3x4 methods (using PAML's terminology). These last two options calculate the codon frequencies as the product of the frequencies of the three nucleotides that make up each codon. In the F1x4 case the nucleotide frequencies are those observed in the dataset across all codon positions, while the F3x4 option uses the nucleotide frequencies observed in the data at each codon position separately. The final component of the codon models is the nonsynonymous to synonymous relative rate parameters (aka dN/dS or omega parameters). The default is to infer a single dN/dS value. Alternatively, a model can be specified that infers a given number of dN/dS categories, with the dN/dS values and proportions falling in each category estimated (ratehetmodel = nonsynonymous). This is the discrete or M3 model in PAML's terminology. From the Author: No stop codons under the chosen genetic code are allowed. These are: standard code (TAG, TAA and TGA); vertebrate mitochondria (TAG, TAA, AGA and AGG); invertebrate mitochondria (TAG and TAA). One might argue that stop codons should just be ignored and treated as missing, but this can be dangerous. Sometimes they will come from a sequencing error, but more often from an alignment problem, an incorrectly chosen genetic code, or a sequence that is not really coding (e.g. an intron). In any case, error should be examined and resolved consciously by the user. One thing to note is that codon models for tree inference require that you align the protein coding sequences along a correct reading frame; (e.g., gaps of 1 or 2 bases will impair the analysis). Maintaining the reading frame makes alignment much easier even if your analysis will be at the nucleotide level. Just running sequences through a sequence alignment program without looking is almost guaranteed to return an alignment that will not work for codon based inference. The other important restriction to note is that GARLI expects the alignment to begin on the first base of a codon. It can't figure out where the reading frame is, so if the alignment starts with a partial codon it needs to be removed or excluded from the alignment. Version 0.96 does allow normal NEXUS exclusions through an assumptions block, so the following would work to exclude the first two bases of an alignment and tell GARLI that the reading frame starts on the third. begin assumptions; exset * myexset = 1 2; end;. c_ratematrix garli.conf 2 Codon Rate Matrix (ratematrix) perl !$configure_partitions && $datatype_value eq "codon" perl "ratematrix = $value\\n" 2rate 1rate 1rate 2rate 2rate 6rate 6rate fixed fixed custom custom string string This determines the relative rates of nucleotide substitution assumed by the codon model. The options are exactly the same as those allowed under a normal nucleotide model. A codon model with ratematrix = 2rate specifies the standard Goldman and Yang (1994) model, with different substitution rates for transitions and transversions. c_statefrequencies garli.conf 2 Codon Frequencies (statefequencies) perl !$configure_partitions && $datatype_value eq "codon" perl "statefrequencies = $value\\n" equal equal empirical empirical (+F) f1x4 F1x4 f3x4 F3x4 f3x4 The options are to use equal codon frequencies (not a good option), the frequencies observed in your dataset (termed empirical in GARLI), or the codon frequencies implied by the F1x4 or F3x4 methods (using PAML's terminology). These last two options calculate the codon frequencies as the product of the frequencies of the three nucleotides that make up each codon. In the F1x4 case the nucleotide frequencies are those observed in the dataset across all codon positions, while the F3x4 option uses the nucleotide frequencies observed in the data at each codon position separately. c_ratehetmodel garli.conf 2 dN/dS categories (or Omega) (ratehetmodel) perl !$configure_partitions && $datatype_value eq "codon" none A single dN/dS parameter (none) nonsynonymous discrete or M3 model (nonsynonymous) none "ratehetmodel = none\\ninvariantsites = none\\nnumratecats = 1\\n" nonsynonymous "ratehetmodel = nonsynonymous\\ninvariantsites = none\\n" none For codon models, the default is to infer a single dN/dS parameter. Alternatively, a model can be specified that infers a given number of dN/dS categories, with the dN/dS values and proportions falling in each category estimated (ratehetmodel = nonsynonymous). This is the discrete or M3 model of Yang et al. (2000). c_numratecats Number of dN/dS parameter categories (numratecats) perl !$configure_partitions && $datatype_value eq "codon" && $c_ratehetmodel eq "nonsynonymous" perl "numratecats = $value\\n" 3 Number of rate categories: must be an integer between 1 and 8 perl $c_numratecats < 1 || $c_numratecats > 8 2 garli.conf When ratehetmodel = nonsynonymous, this is the number of dN/dS parameter categories. model1 Model Parameters for Partition 1 datatype_value1 The type of data (datatype) perl $configure_partitions nucleotide nucleotide nucleotide aminoacid amino acid codon-aminoacid codon-aminoacid codon codon nucleotide "datatype = nucleotide\\n" aminoacid "datatype = aminoacid\\n" codon-aminoacid "datatype = codon-aminoacid\\n" codon "datatype = codon\\n" garli.conf 6 The codon-aminoacid datatype means that the data will be supplied as a nucleotide alignment, but will be internally translated and analyzed using an amino acid model. The codon and codon-aminoacid datatypes require nucleotide sequence that is aligned in the correct reading frame. In other words, all gaps in the alignment should be a multiple of 3 in length, and the alignment should start at the first position of a codon. If the alignment has extra columns at the start, middle or end, they should be removed or excluded with a Nexus exset (see the FAQ for an example of exset usage). The correct geneticcode must also be set. geneticcode_value1 Select the Genetic Code (geneticcode) perl $configure_partitions && ($datatype_value1 eq "codon" || $datatype_value1 eq "codon-aminoacid") perl "geneticcode = $value\\n" standard Standard vertmito Vertebrate Mitochondria invertmito Invertebrate Mitochondria standard garli.conf 6 The codon-aminoacid datatype means that the data will be supplied as a nucleotide alignment, but will be internally translated and analyzed using an amino acid model. The codon and codon-aminoacid datatypes require nucleotide sequence that is aligned in the correct reading frame. In other words, all gaps in the alignment should be a multiple of 3 in length, and the alignment should start at the first position of a codon. If the alignment has extra columns at the start, middle or end, they should be removed or excluded with a Nexus exset (see the FAQ for an example of exset usage). The correct geneticcode must also be set. model_nucleotide1 Nucleotide Model JC (Jukes-Cantor model): Rate Matrix = 1 rate, Base Frequencies = equal K2P (Kimura 2-Parameter model): Rate Matrix = 2 rate, Base Frequencies = equal F81 (Felsenstein 1981 model): Rate Matrix = 1 rate, Base Frequencies = estimate HKY (Hasegawa, Kishino and Yano model): Rate Matrix = 2 rate, Base Frequencies = estimate GTR (General Time-Reversible model): Rate Matrix = 6 rate, Base Frequencies = estimate d_ratematrix1 garli.conf Rate Matrix (ratematrix) perl $configure_partitions && $datatype_value1 eq "nucleotide" 1rate All Rates Equal (1rate) 2rate HKY (2rate) 6rate General time-reversible (6 rate) fixed fixed rate custom_string User Specified 1rate "ratematrix = $value\\n" 2rate "ratematrix = $value\\n" 6rate "ratematrix = $value\\n" fixed "ratematrix = $value\\n" custom_string "ratematrix = ($ACsubrates1 $AGsubrates1 $ATsubrates1 $CGsubrates1 $CTsubrates1 $GTsubrates1)\\n" 6rate garli.conf 6 New in version 0.96, parameters for any submodel of the GTR model may now be estimated. The format for specifying this is very similar to that used in the rclass setting of PAUP*. Within parentheses, six letters are specified, with spaces between them. The six letters represent the rates of substitution between the six pairs of nucleotides, with the order being A-C, A-G, A-T, C-G, C-T and G-T. Letters within the parentheses that are the same mean that a single parameter is shared by multiple nucleotide pairs. For example, ratematrix = (a b a a b a) would specify the HKY 2-rate model (equivalent to ratematrix = 2rate). This entry, ratematrix = (a b c c b a) would specify 3 estimated rates of substitution, with one rate shared by A-C and G-T substitutions, another rate shared by A-G and C-T substitutions, and the final rate shared by A-T and C-G substitutions. ACsubrates1 User specified AC substitution rates (custom ratematrix) perl $configure_partitions && $datatype_value1 eq "nucleotide" && $d_ratematrix1 eq "custom_string" perl "" AGsubrates1 User specified AG substitution rates (custom ratematrix) perl $configure_partitions && $datatype_value1 eq "nucleotide" && $d_ratematrix1 eq "custom_string" perl "" ATsubrates1 User specified AT substitution rates (custom ratematrix) perl $configure_partitions && $datatype_value1 eq "nucleotide" && $d_ratematrix1 eq "custom_string" perl "" CGsubrates1 User specified CG substitution rates (custom ratematrix) perl $configure_partitions && $datatype_value1 eq "nucleotide" && $d_ratematrix1 eq "custom_string" perl "" CTsubrates1 User specified CT subsitution rates (custom ratematrix) perl $configure_partitions && $datatype_value1 eq "nucleotide" && $d_ratematrix1 eq "custom_string" perl "" GTsubrates1 User specified GT substitution rates (custom ratematrix) perl $configure_partitions && $datatype_value1 eq "nucleotide" && $d_ratematrix1 eq "custom_string" perl "" d_statefrequencies1 garli.conf Base Frequencies (statefrequencies) perl $configure_partitions && $datatype_value1 eq "nucleotide" perl "statefrequencies = $value\\n" equal equal empirical empirical estimate estimate fixed fixed estimate garli.conf 6 d_invariantsites1 garli.conf Proportion of invariant sites (invariantsites) perl $configure_partitions && $datatype_value1 eq "nucleotide" perl "invariantsites = $value\\n" none none estimate estimate estimate 6 garli.conf Specifies whether a parameter representing the proportion of sites that are unable to change (i.e. have a substitution rate of zero) will be included. This is typically referred to as invariant sites, but would better be termed invariable sites. d_ratehetmodel1 garli.conf The model of rate heterogeneity (ratehetmodel) perl $configure_partitions && $datatype_value1 eq "nucleotide" perl ($d_ratehetmodel1 eq "none") ? "numratecats = 1\\nratehetmodel = $value\\n" : "numratecats = $d_numratecats1\\nratehetmodel = $value\\n" none Equal Rates For All Sites (none) gamma Gamma Distribution (gamma) gamma garli.conf 6 The model of rate heterogeneity assumed. gammafixed requires that the alpha shape parameter is provided, and a setting of gamma estimates it. d_numratecats1 Number of rate categories (numratecats) perl $configure_partitions && $datatype_value1 eq "nucleotide" && $d_ratehetmodel1 eq "gamma" perl "numratecats=$value\\n" 4 :Number of rate categories: must be an integer between 1 and 20 perl $d_numratecats1 < 2 || $d_numratecats1 > 20 garli.conf 6 The number of categories of variable rates (not including the invariant site class if it is being used). Must be set to 1 if ratehetmodel is set to none. Note that runtimes and memory usage scale linearly with this setting. model_protein1 Protein Model dayhoff Dayhoff, Schwartz and Orcutt. 1978 jones Jones, Taylor and Thornton (JTT), 1992 WAG Whelan and Goldman, 2001 mtREV Adachi and Hasegawa, 1996 mtmam Yang, Nielsen and Hasegawa. 1998 p_ratematrix1 garli.conf 6 Protein Rate Matrix (ratematrix) perl $configure_partitions && ($datatype_value1 eq "aminoacid" || $datatype_value1 eq "codon-aminoacid") perl "ratematrix = $value\\n" wag poisson Poisson jones Jones dayhoff Dayhoff wag WAG mtmam mtMAM mtrev mtREV You should use the matrix that gives the best likelihood, and could use a program like PROTTEST (very much like MODELTEST, but for amino acid models) to determine which fits best for your data. Poisson assumes a single rate of substitution between all amino acid pairs, and is a very poor model. p_statefrequencies1 garli.conf 6 Amino Acid Frequencies (statefequencies) perl $configure_partitions && ($datatype_value1 eq "aminoacid" || $datatype_value1 eq "codon-aminoacid") perl "statefrequencies = $value\\n" equal equal empirical empirical (+F) estimate estimate fixed fixed jones Jones dayhoff Dayhoff wag WAG mtmam mtMAM mtrev mtREV empirical Specifies how the equilibrium state frequencies of the 20 amino acids are treated. The empirical option fixes the frequencies at their observed proportions (when describing a model this is often termed +F). p_invariantsites1 garli.conf 6 Proportion of invariable sites (invariantsites) perl $configure_partitions && ($datatype_value1 eq "aminoacid" || $datatype_value1 eq "codon-aminoacid") perl "invariantsites = $value\\n" none none estimate estimate estimate Specifies whether a parameter representing the proportion of sites that are unable to change (i.e. have a substitution rate of zero) will be included. This is typically referred to as invariant sites, but would better be termed invariable sites. p_ratehetmodel1 garli.conf 6 Model of rate heterogeneity (ratehetmodel) perl $configure_partitions && ($datatype_value1 eq "aminoacid" || $datatype_value1 eq "codon-aminoacid") perl ($p_ratehetmodel1 eq "none") ? "numratecats = 1\\nratehetmodel = $value\\n" : "numratecats = $p_numratecats1\\nratehetmodel = $value\\n" none Equal Rates For All Sites (none) gamma Gamma Distribution (gamma) gamma The model of rate heterogeneity assumed. gammafixed requires that the alpha shape parameter is provided, and a setting of gamma estimates it. p_numratecats1 garli.conf 6 Number of rate categories (numratecats; set at no more than 8) perl $configure_partitions && ($datatype_value1 eq "aminoacid" || $datatype_value1 eq "codon-aminoacid") && $p_ratehetmodel1 eq "gamma" perl "numratecats=$value\\n" 4 Number of rate categories: must be an integer between 1 and 20 perl $p_numratecats1 < 2 || $p_numratecats1 > 20 The number of categories of variable rates (not including the invariant site class if it is being used). Must be set to 1 if ratehetmodel is set to none. Note that runtimes and memory usage scale linearly with this setting. model_codon1 Codon Model The codon models are built with three components: (1) parameters describing the process of individual nucleotide substitutions, (2) equilibrium codon frequencies, and (3) parameters describing the relative rate of nonsynonymous to synonymous substitutions. The nucleotide substitution parameters within the codon models are exactly the same as those possible with standard nucleotide models in GARLI, and are specified with the ratematrix configuration entry. Thus, they can be of the 2rate variety (inferring different rates for transitions and transversions, K2P or HKY-like), the 6rate variety (inferring different rates for all nucleotide pairs, GTR-like) or any other sub-model of GTR. The options for codon frequencies are specified with the statefrequencies configuration entry. The options are to use equal frequencies (not a good option), the frequencies observed in your dataset (termed empirical in GARLI), or the codon frequencies implied by the F1x4 or F3x4 methods (using PAML's terminology). These last two options calculate the codon frequencies as the product of the frequencies of the three nucleotides that make up each codon. In the F1x4 case the nucleotide frequencies are those observed in the dataset across all codon positions, while the F3x4 option uses the nucleotide frequencies observed in the data at each codon position separately. The final component of the codon models is the nonsynonymous to synonymous relative rate parameters (aka dN/dS or omega parameters). The default is to infer a single dN/dS value. Alternatively, a model can be specified that infers a given number of dN/dS categories, with the dN/dS values and proportions falling in each category estimated (ratehetmodel = nonsynonymous). This is the discrete or M3 model in PAML's terminology. From the Author: No stop codons under the chosen genetic code are allowed. These are: standard code (TAG, TAA and TGA); vertebrate mitochondria (TAG, TAA, AGA and AGG); invertebrate mitochondria (TAG and TAA). One might argue that stop codons should just be ignored and treated as missing, but this can be dangerous. Sometimes they will come from a sequencing error, but more often from an alignment problem, an incorrectly chosen genetic code, or a sequence that is not really coding (e.g. an intron). In any case, error should be examined and resolved consciously by the user. One thing to note is that codon models for tree inference require that you align the protein coding sequences along a correct reading frame; (e.g., gaps of 1 or 2 bases will impair the analysis). Maintaining the reading frame makes alignment much easier even if your analysis will be at the nucleotide level. Just running sequences through a sequence alignment program without looking is almost guaranteed to return an alignment that will not work for codon based inference. The other important restriction to note is that GARLI expects the alignment to begin on the first base of a codon. It can't figure out where the reading frame is, so if the alignment starts with a partial codon it needs to be removed or excluded from the alignment. Version 0.96 does allow normal NEXUS exclusions through an assumptions block, so the following would work to exclude the first two bases of an alignment and tell GARLI that the reading frame starts on the third. begin assumptions; exset * myexset = 1 2; end;. c_ratematrix1 garli.conf 6 Codon Rate Matrix (ratematrix) perl $configure_partitions && $datatype_value1 eq "codon" perl "ratematrix = $value\\n" 2rate 1rate 1rate 2rate 2rate 6rate 6rate fixed fixed custom custom string string This determines the relative rates of nucleotide substitution assumed by the codon model. The options are exactly the same as those allowed under a normal nucleotide model. A codon model with ratematrix = 2rate specifies the standard Goldman and Yang (1994) model, with different substitution rates for transitions and transversions. c_statefrequencies1 garli.conf 6 Codon Frequencies (statefequencies) perl $configure_partitions && $datatype_value1 eq "codon" perl "statefrequencies = $value\\n" equal equal empirical empirical (+F) f1x4 F1x4 f3x4 F3x4 f3x4 The options are to use equal codon frequencies (not a good option), the frequencies observed in your dataset (termed empirical in GARLI), or the codon frequencies implied by the F1x4 or F3x4 methods (using PAML's terminology). These last two options calculate the codon frequencies as the product of the frequencies of the three nucleotides that make up each codon. In the F1x4 case the nucleotide frequencies are those observed in the dataset across all codon positions, while the F3x4 option uses the nucleotide frequencies observed in the data at each codon position separately. c_ratehetmodel1 garli.conf 6 dN/dS categories (or Omega) (ratehetmodel) perl $configure_partitions && $datatype_value1 eq "codon" none A single dN/dS parameter (none) nonsynonymous discrete or M3 model (nonsynonymous) none "ratehetmodel = none\\ninvariantsites = none\\nnumratecats = 1\\n" nonsynonymous "ratehetmodel = nonsynonymous\\ninvariantsites = none\\n" none For codon models, the default is to infer a single dN/dS parameter. Alternatively, a model can be specified that infers a given number of dN/dS categories, with the dN/dS values and proportions falling in each category estimated (ratehetmodel = nonsynonymous). This is the discrete or M3 model of Yang et al. (2000). c_numratecats1 Number of dN/dS parameter categories (numratecats) perl $configure_partitions && $datatype_value1 eq "codon" && $c_ratehetmodel1 eq "nonsynonymous" perl "numratecats = $value\\n" 3 Number of rate categories: must be an integer between 1 and 8 perl $c_numratecats1 < 1 || $c_numratecats1 > 8 6 garli.conf When ratehetmodel = nonsynonymous, this is the number of dN/dS parameter categories. model2 Model Parameters for Partition 2 datatype_value2 The type of data (datatype) perl $configure_partitions nucleotide nucleotide nucleotide aminoacid amino acid codon-aminoacid codon-aminoacid codon codon nucleotide "datatype = nucleotide\\n" aminoacid "datatype = aminoacid\\n" codon-aminoacid "datatype = codon-aminoacid\\n" codon "datatype = codon\\n" garli.conf 8 The codon-aminoacid datatype means that the data will be supplied as a nucleotide alignment, but will be internally translated and analyzed using an amino acid model. The codon and codon-aminoacid datatypes require nucleotide sequence that is aligned in the correct reading frame. In other words, all gaps in the alignment should be a multiple of 3 in length, and the alignment should start at the first position of a codon. If the alignment has extra columns at the start, middle or end, they should be removed or excluded with a Nexus exset (see the FAQ for an example of exset usage). The correct geneticcode must also be set. geneticcode_value2 Select the Genetic Code (geneticcode) perl $datatype_value2 eq "codon" || $datatype_value2 eq "codon-aminoacid" perl "geneticcode = $value\\n" standard Standard vertmito Vertebrate Mitochondria invertmito Invertebrate Mitochondria standard garli.conf 8 The codon-aminoacid datatype means that the data will be supplied as a nucleotide alignment, but will be internally translated and analyzed using an amino acid model. The codon and codon-aminoacid datatypes require nucleotide sequence that is aligned in the correct reading frame. In other words, all gaps in the alignment should be a multiple of 3 in length, and the alignment should start at the first position of a codon. If the alignment has extra columns at the start, middle or end, they should be removed or excluded with a Nexus exset (see the FAQ for an example of exset usage). The correct geneticcode must also be set. model_nucleotide2 Nucleotide Model JC (Jukes-Cantor model): Rate Matrix = 1 rate, Base Frequencies = equal K2P (Kimura 2-Parameter model): Rate Matrix = 2 rate, Base Frequencies = equal F81 (Felsenstein 1981 model): Rate Matrix = 1 rate, Base Frequencies = estimate HKY (Hasegawa, Kishino and Yano model): Rate Matrix = 2 rate, Base Frequencies = estimate GTR (General Time-Reversible model): Rate Matrix = 6 rate, Base Frequencies = estimate d_ratematrix2 garli.conf Rate Matrix (ratematrix) perl $configure_partitions && $datatype_value2 eq "nucleotide" 1rate All Rates Equal (1rate) 2rate HKY (2rate) 6rate General time-reversible (6 rate) fixed fixed rate custom_string User Specified 1rate "ratematrix = $value\\n" 2rate "ratematrix = $value\\n" 6rate "ratematrix = $value\\n" fixed "ratematrix = $value\\n" custom_string "ratematrix = ($ACsubrates2 $AGsubrates2 $ATsubrates2 $CGsubrates2 $CTsubrates2 $GTsubrates2)\\n" 6rate garli.conf 8 New in version 0.96, parameters for any submodel of the GTR model may now be estimated. The format for specifying this is very similar to that used in the rclass setting of PAUP*. Within parentheses, six letters are specified, with spaces between them. The six letters represent the rates of substitution between the six pairs of nucleotides, with the order being A-C, A-G, A-T, C-G, C-T and G-T. Letters within the parentheses that are the same mean that a single parameter is shared by multiple nucleotide pairs. For example, ratematrix = (a b a a b a) would specify the HKY 2-rate model (equivalent to ratematrix = 2rate). This entry, ratematrix = (a b c c b a) would specify 3 estimated rates of substitution, with one rate shared by A-C and G-T substitutions, another rate shared by A-G and C-T substitutions, and the final rate shared by A-T and C-G substitutions. ACsubrates2 User specified AC substitution rates (custom ratematrix) perl $configure_partitions && $datatype_value2 eq "nucleotide" && $d_ratematrix2 eq "custom_string" perl "" AGsubrates2 User specified AG substitution rates (custom ratematrix) perl $configure_partitions && $datatype_value2 eq "nucleotide" && $d_ratematrix2 eq "custom_string" perl "" ATsubrates2 User specified AT substitution rates (custom ratematrix) perl $configure_partitions && $datatype_value2 eq "nucleotide" && $d_ratematrix2 eq "custom_string" perl "" CGsubrates2 User specified CG substitution rates (custom ratematrix) perl $configure_partitions && $datatype_value2 eq "nucleotide" && $d_ratematrix2 eq "custom_string" perl "" CTsubrates2 User specified CT subsitution rates (custom ratematrix) perl $configure_partitions && $datatype_value2 eq "nucleotide" && $d_ratematrix2 eq "custom_string" perl "" GTsubrates2 User specified GT substitution rates (custom ratematrix) perl $configure_partitions && $datatype_value2 eq "nucleotide" && $d_ratematrix2 eq "custom_string" perl "" d_statefrequencies2 garli.conf Base Frequencies (statefrequencies) perl $configure_partitions && $datatype_value2 eq "nucleotide" perl "statefrequencies = $value\\n" equal equal empirical empirical estimate estimate fixed fixed estimate garli.conf 8 d_invariantsites2 garli.conf Proportion of invariant sites (invariantsites) perl $configure_partitions && $datatype_value2 eq "nucleotide" perl "invariantsites = $value\\n" none none estimate estimate estimate 8 garli.conf Specifies whether a parameter representing the proportion of sites that are unable to change (i.e. have a substitution rate of zero) will be included. This is typically referred to as invariant sites, but would better be termed invariable sites. d_ratehetmodel2 garli.conf The model of rate heterogeneity (ratehetmodel) perl $configure_partitions && $datatype_value2 eq "nucleotide" perl ($d_ratehetmodel2 eq "none") ? "numratecats = 1\\nratehetmodel = $value\\n" : "numratecats = $d_numratecats2\\nratehetmodel = $value\\n" none Equal Rates For All Sites (none) gamma Gamma Distribution (gamma) gamma garli.conf 8 The model of rate heterogeneity assumed. gammafixed requires that the alpha shape parameter is provided, and a setting of gamma estimates it. d_numratecats2 Number of rate categories (numratecats) perl $configure_partitions && $datatype_value2 eq "nucleotide" && $d_ratehetmodel2 eq "gamma" perl "numratecats=$value\\n" 4 :Number of rate categories: must be an integer between 1 and 20 perl $d_numratecats2 < 2 || $d_numratecats2 > 20 garli.conf 8 The number of categories of variable rates (not including the invariant site class if it is being used). Must be set to 1 if ratehetmodel is set to none. Note that runtimes and memory usage scale linearly with this setting. model_protein2 Protein Model dayhoff Dayhoff, Schwartz and Orcutt. 1978 jones Jones, Taylor and Thornton (JTT), 1992 WAG Whelan and Goldman, 2001 mtREV Adachi and Hasegawa, 1996 mtmam Yang, Nielsen and Hasegawa. 1998 p_ratematrix2 garli.conf 8 Protein Rate Matrix (ratematrix) perl $configure_partitions && ($datatype_value2 eq "aminoacid" || $datatype_value2 eq "codon-aminoacid") perl "ratematrix = $value\\n" wag poisson Poisson jones Jones dayhoff Dayhoff wag WAG mtmam mtMAM mtrev mtREV You should use the matrix that gives the best likelihood, and could use a program like PROTTEST (very much like MODELTEST, but for amino acid models) to determine which fits best for your data. Poisson assumes a single rate of substitution between all amino acid pairs, and is a very poor model. p_statefrequencies2 garli.conf 8 Amino Acid Frequencies (statefequencies) perl $configure_partitions && ($datatype_value2 eq "aminoacid" || $datatype_value2 eq "codon-aminoacid") perl "statefrequencies = $value\\n" equal equal empirical empirical (+F) estimate estimate fixed fixed jones Jones dayhoff Dayhoff wag WAG mtmam mtMAM mtrev mtREV empirical Specifies how the equilibrium state frequencies of the 20 amino acids are treated. The empirical option fixes the frequencies at their observed proportions (when describing a model this is often termed +F). p_invariantsites2 garli.conf 8 Proportion of invariable sites (invariantsites) perl $configure_partitions && ($datatype_value2 eq "aminoacid" || $datatype_value2 eq "codon-aminoacid") perl "invariantsites = $value\\n" none none estimate estimate estimate Specifies whether a parameter representing the proportion of sites that are unable to change (i.e. have a substitution rate of zero) will be included. This is typically referred to as invariant sites, but would better be termed invariable sites. p_ratehetmodel2 garli.conf 8 Model of rate heterogeneity (ratehetmodel) perl $configure_partitions && ($datatype_value2 eq "aminoacid" || $datatype_value2 eq "codon-aminoacid") perl ($p_ratehetmodel2 eq "none") ? "numratecats = 1\\nratehetmodel = $value\\n" : "numratecats = $p_numratecats2\\nratehetmodel = $value\\n" none Equal Rates For All Sites (none) gamma Gamma Distribution (gamma) gamma The model of rate heterogeneity assumed. gammafixed requires that the alpha shape parameter is provided, and a setting of gamma estimates it. p_numratecats2 garli.conf 8 Number of rate categories (numratecats; set at no more than 8) perl $configure_partitions && ($datatype_value2 eq "aminoacid" || $datatype_value2 eq "codon-aminoacid") && $p_ratehetmodel eq "gamma" perl "numratecats=$value\\n" 4 Number of rate categories: must be an integer between 1 and 20 perl $p_numratecats2 < 2 || $p_numratecats2 > 20 The number of categories of variable rates (not including the invariant site class if it is being used). Must be set to 1 if ratehetmodel is set to none. Note that runtimes and memory usage scale linearly with this setting. model_codon2 Codon Model The codon models are built with three components: (1) parameters describing the process of individual nucleotide substitutions, (2) equilibrium codon frequencies, and (3) parameters describing the relative rate of nonsynonymous to synonymous substitutions. The nucleotide substitution parameters within the codon models are exactly the same as those possible with standard nucleotide models in GARLI, and are specified with the ratematrix configuration entry. Thus, they can be of the 2rate variety (inferring different rates for transitions and transversions, K2P or HKY-like), the 6rate variety (inferring different rates for all nucleotide pairs, GTR-like) or any other sub-model of GTR. The options for codon frequencies are specified with the statefrequencies configuration entry. The options are to use equal frequencies (not a good option), the frequencies observed in your dataset (termed empirical in GARLI), or the codon frequencies implied by the F1x4 or F3x4 methods (using PAML's terminology). These last two options calculate the codon frequencies as the product of the frequencies of the three nucleotides that make up each codon. In the F1x4 case the nucleotide frequencies are those observed in the dataset across all codon positions, while the F3x4 option uses the nucleotide frequencies observed in the data at each codon position separately. The final component of the codon models is the nonsynonymous to synonymous relative rate parameters (aka dN/dS or omega parameters). The default is to infer a single dN/dS value. Alternatively, a model can be specified that infers a given number of dN/dS categories, with the dN/dS values and proportions falling in each category estimated (ratehetmodel = nonsynonymous). This is the discrete or M3 model in PAML's terminology. From the Author: No stop codons under the chosen genetic code are allowed. These are: standard code (TAG, TAA and TGA); vertebrate mitochondria (TAG, TAA, AGA and AGG); invertebrate mitochondria (TAG and TAA). One might argue that stop codons should just be ignored and treated as missing, but this can be dangerous. Sometimes they will come from a sequencing error, but more often from an alignment problem, an incorrectly chosen genetic code, or a sequence that is not really coding (e.g. an intron). In any case, error should be examined and resolved consciously by the user. One thing to note is that codon models for tree inference require that you align the protein coding sequences along a correct reading frame; (e.g., gaps of 1 or 2 bases will impair the analysis). Maintaining the reading frame makes alignment much easier even if your analysis will be at the nucleotide level. Just running sequences through a sequence alignment program without looking is almost guaranteed to return an alignment that will not work for codon based inference. The other important restriction to note is that GARLI expects the alignment to begin on the first base of a codon. It can't figure out where the reading frame is, so if the alignment starts with a partial codon it needs to be removed or excluded from the alignment. Version 0.96 does allow normal NEXUS exclusions through an assumptions block, so the following would work to exclude the first two bases of an alignment and tell GARLI that the reading frame starts on the third. begin assumptions; exset * myexset = 1 2; end;. c_ratematrix2 garli.conf 8 Codon Rate Matrix (ratematrix) perl $configure_partitions && $datatype_value2 eq "codon" perl "ratematrix = $value\\n" 2rate 1rate 1rate 2rate 2rate 6rate 6rate fixed fixed custom custom string string This determines the relative rates of nucleotide substitution assumed by the codon model. The options are exactly the same as those allowed under a normal nucleotide model. A codon model with ratematrix = 2rate specifies the standard Goldman and Yang (1994) model, with different substitution rates for transitions and transversions. c_statefrequencies2 garli.conf 8 Codon Frequencies (statefequencies) perl $configure_partitions && $datatype_value2 eq "codon" perl "statefrequencies = $value\\n" equal equal empirical empirical (+F) f1x4 F1x4 f3x4 F3x4 f3x4 The options are to use equal codon frequencies (not a good option), the frequencies observed in your dataset (termed empirical in GARLI), or the codon frequencies implied by the F1x4 or F3x4 methods (using PAML's terminology). These last two options calculate the codon frequencies as the product of the frequencies of the three nucleotides that make up each codon. In the F1x4 case the nucleotide frequencies are those observed in the dataset across all codon positions, while the F3x4 option uses the nucleotide frequencies observed in the data at each codon position separately. c_ratehetmodel2 garli.conf 8 dN/dS categories (or Omega) (ratehetmodel) perl $configure_partitions && $datatype_value2 eq "codon" none A single dN/dS parameter (none) nonsynonymous discrete or M3 model (nonsynonymous) none "ratehetmodel = none\\ninvariantsites = none\\nnumratecats = 1\\n" nonsynonymous "ratehetmodel = nonsynonymous\\ninvariantsites = none\\n" none For codon models, the default is to infer a single dN/dS parameter. Alternatively, a model can be specified that infers a given number of dN/dS categories, with the dN/dS values and proportions falling in each category estimated (ratehetmodel = nonsynonymous). This is the discrete or M3 model of Yang et al. (2000). c_numratecats2 Number of dN/dS parameter categories (numratecats) perl $configure_partitions && $datatype_value2 eq "codon" && $c_ratehetmodel2 eq "nonsynonymous" perl "numratecats = $value\\n" 3 Number of rate categories: must be an integer between 1 and 8 perl $c_numratecats2 < 1 || $c_numratecats2 > 8 8 garli.conf When ratehetmodel = nonsynonymous, this is the number of dN/dS parameter categories. model3 Model Parameters for Partition 3 datatype_value3 The type of data (datatype) perl $numparts > 2 nucleotide nucleotide nucleotide aminoacid amino acid codon-aminoacid codon-aminoacid codon codon nucleotide "datatype = nucleotide\\n" aminoacid "datatype = aminoacid\\n" codon-aminoacid "datatype = codon-aminoacid\\n" codon "datatype = codon\\n" garli.conf 10 The codon-aminoacid datatype means that the data will be supplied as a nucleotide alignment, but will be internally translated and analyzed using an amino acid model. The codon and codon-aminoacid datatypes require nucleotide sequence that is aligned in the correct reading frame. In other words, all gaps in the alignment should be a multiple of 3 in length, and the alignment should start at the first position of a codon. If the alignment has extra columns at the start, middle or end, they should be removed or excluded with a Nexus exset (see the FAQ for an example of exset usage). The correct geneticcode must also be set. geneticcode_value3 Select the Genetic Code (geneticcode) perl $numparts > 2 && ($datatype_value3 eq "codon" || $datatype_value3 eq "codon-aminoacid") perl "geneticcode = $value\\n" standard Standard vertmito Vertebrate Mitochondria invertmito Invertebrate Mitochondria standard garli.conf 10 The codon-aminoacid datatype means that the data will be supplied as a nucleotide alignment, but will be internally translated and analyzed using an amino acid model. The codon and codon-aminoacid datatypes require nucleotide sequence that is aligned in the correct reading frame. In other words, all gaps in the alignment should be a multiple of 3 in length, and the alignment should start at the first position of a codon. If the alignment has extra columns at the start, middle or end, they should be removed or excluded with a Nexus exset (see the FAQ for an example of exset usage). The correct geneticcode must also be set. model_nucleotide3 Nucleotide Model JC (Jukes-Cantor model): Rate Matrix = 1 rate, Base Frequencies = equal K2P (Kimura 2-Parameter model): Rate Matrix = 2 rate, Base Frequencies = equal F81 (Felsenstein 1981 model): Rate Matrix = 1 rate, Base Frequencies = estimate HKY (Hasegawa, Kishino and Yano model): Rate Matrix = 2 rate, Base Frequencies = estimate GTR (General Time-Reversible model): Rate Matrix = 6 rate, Base Frequencies = estimate d_ratematrix3 garli.conf Rate Matrix (ratematrix) perl $numparts > 2 && $datatype_value3 eq "nucleotide" 1rate All Rates Equal (1rate) 2rate HKY (2rate) 6rate General time-reversible (6 rate) fixed fixed rate custom_string User Specified 1rate "ratematrix = $value\\n" 2rate "ratematrix = $value\\n" 6rate "ratematrix = $value\\n" fixed "ratematrix = $value\\n" custom_string "ratematrix = ($ACsubrates3 $AGsubrates3 $ATsubrates3 $CGsubrates3 $CTsubrates3 $GTsubrates3)\\n" 6rate garli.conf 10 New in version 0.96, parameters for any submodel of the GTR model may now be estimated. The format for specifying this is very similar to that used in the rclass setting of PAUP*. Within parentheses, six letters are specified, with spaces between them. The six letters represent the rates of substitution between the six pairs of nucleotides, with the order being A-C, A-G, A-T, C-G, C-T and G-T. Letters within the parentheses that are the same mean that a single parameter is shared by multiple nucleotide pairs. For example, ratematrix = (a b a a b a) would specify the HKY 2-rate model (equivalent to ratematrix = 2rate). This entry, ratematrix = (a b c c b a) would specify 3 estimated rates of substitution, with one rate shared by A-C and G-T substitutions, another rate shared by A-G and C-T substitutions, and the final rate shared by A-T and C-G substitutions. ACsubrates3 User specified AC substitution rates (custom ratematrix) perl $numparts > 2 && $datatype_value3 eq "nucleotide" && $d_ratematrix3 eq "custom_string" perl "" AGsubrates3 User specified AG substitution rates (custom ratematrix) perl $numparts > 2 && $datatype_value3 eq "nucleotide" && $d_ratematrix3 eq "custom_string" perl "" ATsubrates3 User specified AT substitution rates (custom ratematrix) perl $numparts > 2 && $datatype_value3 eq "nucleotide" && $d_ratematrix3 eq "custom_string" perl "" CGsubrates3 User specified CG substitution rates (custom ratematrix) perl $numparts > 2 && $datatype_value3 eq "nucleotide" && $d_ratematrix3 eq "custom_string" perl "" CTsubrates3 User specified CT subsitution rates (custom ratematrix) perl $numparts > 2 && $datatype_value3 eq "nucleotide" && $d_ratematrix3 eq "custom_string" perl "" GTsubrates3 User specified GT substitution rates (custom ratematrix) perl $numparts > 2 && $datatype_value3 eq "nucleotide" && $d_ratematrix3 eq "custom_string" perl "" d_statefrequencies3 garli.conf Base Frequencies (statefrequencies) perl $numparts > 2 && $datatype_value3 eq "nucleotide" perl "statefrequencies = $value\\n" equal equal empirical empirical estimate estimate fixed fixed estimate garli.conf 10 d_invariantsites3 garli.conf Proportion of invariant sites (invariantsites) perl $numparts > 2 && $datatype_value3 eq "nucleotide" perl "invariantsites = $value\\n" none none estimate estimate estimate 10 garli.conf Specifies whether a parameter representing the proportion of sites that are unable to change (i.e. have a substitution rate of zero) will be included. This is typically referred to as invariant sites, but would better be termed invariable sites. d_ratehetmodel3 garli.conf The model of rate heterogeneity (ratehetmodel) perl $numparts > 2 && $datatype_value3 eq "nucleotide" perl ($d_ratehetmodel3 eq "none") ? "numratecats = 1\\nratehetmodel = $value\\n" : "numratecats = $d_numratecats3\\nratehetmodel = $value\\n" none Equal Rates For All Sites (none) gamma Gamma Distribution (gamma) gamma garli.conf 10 The model of rate heterogeneity assumed. gammafixed requires that the alpha shape parameter is provided, and a setting of gamma estimates it. d_numratecats3 Number of rate categories (numratecats) perl $numparts > 2 && $datatype_value3 eq "nucleotide" && $d_ratehetmodel3 eq "gamma" perl "numratecats=$value\\n" 4 :Number of rate categories: must be an integer between 1 and 20 perl $d_numratecats3 < 2 || $d_numratecats3 > 20 garli.conf 10 The number of categories of variable rates (not including the invariant site class if it is being used). Must be set to 1 if ratehetmodel is set to none. Note that runtimes and memory usage scale linearly with this setting. model_protein3 Protein Model dayhoff Dayhoff, Schwartz and Orcutt. 1978 jones Jones, Taylor and Thornton (JTT), 1992 WAG Whelan and Goldman, 2001 mtREV Adachi and Hasegawa, 1996 mtmam Yang, Nielsen and Hasegawa. 1998 p_ratematrix3 garli.conf 10 Protein Rate Matrix (ratematrix) perl $numparts > 2 && ($datatype_value3 eq "aminoacid" || $datatype_value3 eq "codon-aminoacid") perl "ratematrix = $value\\n" wag poisson Poisson jones Jones dayhoff Dayhoff wag WAG mtmam mtMAM mtrev mtREV You should use the matrix that gives the best likelihood, and could use a program like PROTTEST (very much like MODELTEST, but for amino acid models) to determine which fits best for your data. Poisson assumes a single rate of substitution between all amino acid pairs, and is a very poor model. p_statefrequencies3 garli.conf 10 Amino Acid Frequencies (statefequencies) perl $numparts > 2 && ($datatype_value3 eq "aminoacid" || $datatype_value3 eq "codon-aminoacid") perl "statefrequencies = $value\\n" equal equal empirical empirical (+F) estimate estimate fixed fixed jones Jones dayhoff Dayhoff wag WAG mtmam mtMAM mtrev mtREV empirical Specifies how the equilibrium state frequencies of the 20 amino acids are treated. The empirical option fixes the frequencies at their observed proportions (when describing a model this is often termed +F). p_invariantsites3 garli.conf 10 Proportion of invariable sites (invariantsites) perl $numparts > 2 && ($datatype_value3 eq "aminoacid" || $datatype_value3 eq "codon-aminoacid") perl "invariantsites = $value\\n" none none estimate estimate estimate Specifies whether a parameter representing the proportion of sites that are unable to change (i.e. have a substitution rate of zero) will be included. This is typically referred to as invariant sites, but would better be termed invariable sites. p_ratehetmodel3 garli.conf 10 Model of rate heterogeneity (ratehetmodel) perl $numparts > 2 && ($datatype_value3 eq "aminoacid" || $datatype_value3 eq "codon-aminoacid") perl ($p_ratehetmodel3 eq "none") ? "numratecats = 1\\nratehetmodel = $value\\n" : "numratecats = $p_numratecats3\\nratehetmodel = $value\\n" none Equal Rates For All Sites (none) gamma Gamma Distribution (gamma) gamma The model of rate heterogeneity assumed. gammafixed requires that the alpha shape parameter is provided, and a setting of gamma estimates it. p_numratecats3 garli.conf 10 Number of rate categories (numratecats; set at no more than 8) perl $numparts > 2 && ($datatype_value3 eq "aminoacid" || $datatype_value3 eq "codon-aminoacid") && $p_ratehetmodel eq "gamma" perl "numratecats=$value\\n" 4 Number of rate categories: must be an integer between 1 and 20 perl $p_numratecats3 < 2 || $p_numratecats3 > 20 The number of categories of variable rates (not including the invariant site class if it is being used). Must be set to 1 if ratehetmodel is set to none. Note that runtimes and memory usage scale linearly with this setting. model_codon3 Codon Model The codon models are built with three components: (1) parameters describing the process of individual nucleotide substitutions, (2) equilibrium codon frequencies, and (3) parameters describing the relative rate of nonsynonymous to synonymous substitutions. The nucleotide substitution parameters within the codon models are exactly the same as those possible with standard nucleotide models in GARLI, and are specified with the ratematrix configuration entry. Thus, they can be of the 2rate variety (inferring different rates for transitions and transversions, K2P or HKY-like), the 6rate variety (inferring different rates for all nucleotide pairs, GTR-like) or any other sub-model of GTR. The options for codon frequencies are specified with the statefrequencies configuration entry. The options are to use equal frequencies (not a good option), the frequencies observed in your dataset (termed empirical in GARLI), or the codon frequencies implied by the F1x4 or F3x4 methods (using PAML's terminology). These last two options calculate the codon frequencies as the product of the frequencies of the three nucleotides that make up each codon. In the F1x4 case the nucleotide frequencies are those observed in the dataset across all codon positions, while the F3x4 option uses the nucleotide frequencies observed in the data at each codon position separately. The final component of the codon models is the nonsynonymous to synonymous relative rate parameters (aka dN/dS or omega parameters). The default is to infer a single dN/dS value. Alternatively, a model can be specified that infers a given number of dN/dS categories, with the dN/dS values and proportions falling in each category estimated (ratehetmodel = nonsynonymous). This is the discrete or M3 model in PAML's terminology. From the Author: No stop codons under the chosen genetic code are allowed. These are: standard code (TAG, TAA and TGA); vertebrate mitochondria (TAG, TAA, AGA and AGG); invertebrate mitochondria (TAG and TAA). One might argue that stop codons should just be ignored and treated as missing, but this can be dangerous. Sometimes they will come from a sequencing error, but more often from an alignment problem, an incorrectly chosen genetic code, or a sequence that is not really coding (e.g. an intron). In any case, error should be examined and resolved consciously by the user. One thing to note is that codon models for tree inference require that you align the protein coding sequences along a correct reading frame; (e.g., gaps of 1 or 2 bases will impair the analysis). Maintaining the reading frame makes alignment much easier even if your analysis will be at the nucleotide level. Just running sequences through a sequence alignment program without looking is almost guaranteed to return an alignment that will not work for codon based inference. The other important restriction to note is that GARLI expects the alignment to begin on the first base of a codon. It can't figure out where the reading frame is, so if the alignment starts with a partial codon it needs to be removed or excluded from the alignment. Version 0.96 does allow normal NEXUS exclusions through an assumptions block, so the following would work to exclude the first two bases of an alignment and tell GARLI that the reading frame starts on the third. begin assumptions; exset * myexset = 1 2; end;. c_ratematrix3 garli.conf 10 Codon Rate Matrix (ratematrix) perl $numparts > 2 && $datatype_value3 eq "codon" perl "ratematrix = $value\\n" 2rate 1rate 1rate 2rate 2rate 6rate 6rate fixed fixed custom custom string string This determines the relative rates of nucleotide substitution assumed by the codon model. The options are exactly the same as those allowed under a normal nucleotide model. A codon model with ratematrix = 2rate specifies the standard Goldman and Yang (1994) model, with different substitution rates for transitions and transversions. c_statefrequencies3 garli.conf 10 Codon Frequencies (statefequencies) perl $numparts > 2 && $datatype_value3 eq "codon" perl "statefrequencies = $value\\n" equal equal empirical empirical (+F) f1x4 F1x4 f3x4 F3x4 f3x4 The options are to use equal codon frequencies (not a good option), the frequencies observed in your dataset (termed empirical in GARLI), or the codon frequencies implied by the F1x4 or F3x4 methods (using PAML's terminology). These last two options calculate the codon frequencies as the product of the frequencies of the three nucleotides that make up each codon. In the F1x4 case the nucleotide frequencies are those observed in the dataset across all codon positions, while the F3x4 option uses the nucleotide frequencies observed in the data at each codon position separately. c_ratehetmodel3 garli.conf 10 dN/dS categories (or Omega) (ratehetmodel) perl $numparts > 2 && $datatype_value3 eq "codon" none A single dN/dS parameter (none) nonsynonymous discrete or M3 model (nonsynonymous) none "ratehetmodel = none\\ninvariantsites = none\\nnumratecats = 1\\n" nonsynonymous "ratehetmodel = nonsynonymous\\ninvariantsites = none\\n" none For codon models, the default is to infer a single dN/dS parameter. Alternatively, a model can be specified that infers a given number of dN/dS categories, with the dN/dS values and proportions falling in each category estimated (ratehetmodel = nonsynonymous). This is the discrete or M3 model of Yang et al. (2000). c_numratecats3 Number of dN/dS parameter categories (numratecats) perl $numparts > 2 && $datatype_value3 eq "codon" && $c_ratehetmodel3 eq "nonsynonymous" perl "numratecats = $value\\n" 3 Number of rate categories: must be an integer between 1 and 8 perl $c_numratecats3 < 1 || $c_numratecats3 > 8 10 garli.conf When ratehetmodel = nonsynonymous, this is the number of dN/dS parameter categories. model4 Model Parameters for Partition 4 datatype_value4 The type of data (datatype) perl $numparts > 3 nucleotide nucleotide nucleotide aminoacid amino acid codon-aminoacid codon-aminoacid codon codon nucleotide "datatype = nucleotide\\n" aminoacid "datatype = aminoacid\\n" codon-aminoacid "datatype = codon-aminoacid\\n" codon "datatype = codon\\n" garli.conf 12 The codon-aminoacid datatype means that the data will be supplied as a nucleotide alignment, but will be internally translated and analyzed using an amino acid model. The codon and codon-aminoacid datatypes require nucleotide sequence that is aligned in the correct reading frame. In other words, all gaps in the alignment should be a multiple of 3 in length, and the alignment should start at the first position of a codon. If the alignment has extra columns at the start, middle or end, they should be removed or excluded with a Nexus exset (see the FAQ for an example of exset usage). The correct geneticcode must also be set. geneticcode_value4 Select the Genetic Code (geneticcode) perl $datatype_value4 eq "codon" || $datatype_value4 eq "codon-aminoacid" perl "geneticcode = $value\\n" standard Standard vertmito Vertebrate Mitochondria invertmito Invertebrate Mitochondria standard garli.conf 12 The codon-aminoacid datatype means that the data will be supplied as a nucleotide alignment, but will be internally translated and analyzed using an amino acid model. The codon and codon-aminoacid datatypes require nucleotide sequence that is aligned in the correct reading frame. In other words, all gaps in the alignment should be a multiple of 3 in length, and the alignment should start at the first position of a codon. If the alignment has extra columns at the start, middle or end, they should be removed or excluded with a Nexus exset (see the FAQ for an example of exset usage). The correct geneticcode must also be set. model_nucleotide4 Nucleotide Model JC (Jukes-Cantor model): Rate Matrix = 1 rate, Base Frequencies = equal K2P (Kimura 2-Parameter model): Rate Matrix = 2 rate, Base Frequencies = equal F81 (Felsenstein 1981 model): Rate Matrix = 1 rate, Base Frequencies = estimate HKY (Hasegawa, Kishino and Yano model): Rate Matrix = 2 rate, Base Frequencies = estimate GTR (General Time-Reversible model): Rate Matrix = 6 rate, Base Frequencies = estimate d_ratematrix4 garli.conf Rate Matrix (ratematrix) perl $numparts > 3 && $datatype_value4 eq "nucleotide" 1rate All Rates Equal (1rate) 2rate HKY (2rate) 6rate General time-reversible (6 rate) fixed fixed rate custom_string User Specified 1rate "ratematrix = $value\\n" 2rate "ratematrix = $value\\n" 6rate "ratematrix = $value\\n" fixed "ratematrix = $value\\n" custom_string "ratematrix = ($ACsubrates4 $AGsubrates4 $ATsubrates4 $CGsubrates4 $CTsubrates4 $GTsubrates4)\\n" 6rate garli.conf 12 New in version 0.96, parameters for any submodel of the GTR model may now be estimated. The format for specifying this is very similar to that used in the rclass setting of PAUP*. Within parentheses, six letters are specified, with spaces between them. The six letters represent the rates of substitution between the six pairs of nucleotides, with the order being A-C, A-G, A-T, C-G, C-T and G-T. Letters within the parentheses that are the same mean that a single parameter is shared by multiple nucleotide pairs. For example, ratematrix = (a b a a b a) would specify the HKY 2-rate model (equivalent to ratematrix = 2rate). This entry, ratematrix = (a b c c b a) would specify 3 estimated rates of substitution, with one rate shared by A-C and G-T substitutions, another rate shared by A-G and C-T substitutions, and the final rate shared by A-T and C-G substitutions. ACsubrates4 User specified AC substitution rates (custom ratematrix) perl $numparts > 3 && $datatype_value4 eq "nucleotide" && $d_ratematrix4 eq "custom_string" perl "" AGsubrates4 User specified AG substitution rates (custom ratematrix) perl $numparts > 3 && $datatype_value4 eq "nucleotide" && $d_ratematrix4 eq "custom_string" perl "" ATsubrates4 User specified AT substitution rates (custom ratematrix) perl $numparts > 3 && $datatype_value4 eq "nucleotide" && $d_ratematrix4 eq "custom_string" perl "" CGsubrates4 User specified CG substitution rates (custom ratematrix) perl $numparts > 3 && $datatype_value4 eq "nucleotide" && $d_ratematrix4 eq "custom_string" perl "" CTsubrates4 User specified CT subsitution rates (custom ratematrix) perl $numparts > 3 && $datatype_value4 eq "nucleotide" && $d_ratematrix4 eq "custom_string" perl "" GTsubrates4 User specified GT substitution rates (custom ratematrix) perl $numparts > 3 && $datatype_value4 eq "nucleotide" && $d_ratematrix4 eq "custom_string" perl "" d_statefrequencies4 garli.conf Base Frequencies (statefrequencies) perl $numparts > 3 && $datatype_value4 eq "nucleotide" perl "statefrequencies = $value\\n" equal equal empirical empirical estimate estimate fixed fixed estimate garli.conf 12 d_invariantsites4 garli.conf Proportion of invariant sites (invariantsites) perl $numparts > 3 && $datatype_value4 eq "nucleotide" perl "invariantsites = $value\\n" none none estimate estimate estimate 12 garli.conf Specifies whether a parameter representing the proportion of sites that are unable to change (i.e. have a substitution rate of zero) will be included. This is typically referred to as invariant sites, but would better be termed invariable sites. d_ratehetmodel4 garli.conf The model of rate heterogeneity (ratehetmodel) perl $numparts > 3 && $datatype_value4 eq "nucleotide" perl ($d_ratehetmodel4 eq "none") ? "numratecats = 1\\nratehetmodel = $value\\n" : "numratecats = $d_numratecats4\\nratehetmodel = $value\\n" none Equal Rates For All Sites (none) gamma Gamma Distribution (gamma) gamma garli.conf 12 The model of rate heterogeneity assumed. gammafixed requires that the alpha shape parameter is provided, and a setting of gamma estimates it. d_numratecats4 Number of rate categories (numratecats) perl $numparts > 3 && $datatype_value4 eq "nucleotide" && $d_ratehetmodel4 eq "gamma" perl "numratecats=$value\\n" 4 :Number of rate categories: must be an integer between 1 and 20 perl $d_numratecats4 < 2 || $d_numratecats4 > 20 garli.conf 12 The number of categories of variable rates (not including the invariant site class if it is being used). Must be set to 1 if ratehetmodel is set to none. Note that runtimes and memory usage scale linearly with this setting. model_protein4 Protein Model dayhoff Dayhoff, Schwartz and Orcutt. 1978 jones Jones, Taylor and Thornton (JTT), 1992 WAG Whelan and Goldman, 2001 mtREV Adachi and Hasegawa, 1996 mtmam Yang, Nielsen and Hasegawa. 1998 p_ratematrix4 garli.conf 12 Protein Rate Matrix (ratematrix) perl $numparts > 3 && ($datatype_value4 eq "aminoacid" || $datatype_value4 eq "codon-aminoacid") perl "ratematrix = $value\\n" wag poisson Poisson jones Jones dayhoff Dayhoff wag WAG mtmam mtMAM mtrev mtREV You should use the matrix that gives the best likelihood, and could use a program like PROTTEST (very much like MODELTEST, but for amino acid models) to determine which fits best for your data. Poisson assumes a single rate of substitution between all amino acid pairs, and is a very poor model. p_statefrequencies4 garli.conf 12 Amino Acid Frequencies (statefequencies) perl $numparts > 3 && ($datatype_value4 eq "aminoacid" || $datatype_value4 eq "codon-aminoacid") perl "statefrequencies = $value\\n" equal equal empirical empirical (+F) estimate estimate fixed fixed jones Jones dayhoff Dayhoff wag WAG mtmam mtMAM mtrev mtREV empirical Specifies how the equilibrium state frequencies of the 20 amino acids are treated. The empirical option fixes the frequencies at their observed proportions (when describing a model this is often termed +F). p_invariantsites4 garli.conf 12 Proportion of invariable sites (invariantsites) perl $numparts > 3 && ($datatype_value4 eq "aminoacid" || $datatype_value4 eq "codon-aminoacid") perl "invariantsites = $value\\n" none none estimate estimate estimate Specifies whether a parameter representing the proportion of sites that are unable to change (i.e. have a substitution rate of zero) will be included. This is typically referred to as invariant sites, but would better be termed invariable sites. p_ratehetmodel4 garli.conf 12 Model of rate heterogeneity (ratehetmodel) perl $numparts > 3 && ($datatype_value4 eq "aminoacid" || $datatype_value4 eq "codon-aminoacid") perl ($p_ratehetmodel4 eq "none") ? "numratecats = 1\\nratehetmodel = $value\\n" : "numratecats = $p_numratecats4\\nratehetmodel = $value\\n" none Equal Rates For All Sites (none) gamma Gamma Distribution (gamma) gamma The model of rate heterogeneity assumed. gammafixed requires that the alpha shape parameter is provided, and a setting of gamma estimates it. p_numratecats4 garli.conf 12 Number of rate categories (numratecats; set at no more than 8) perl $numparts > 3 && ($datatype_value4 eq "aminoacid" || $datatype_value4 eq "codon-aminoacid") && $p_ratehetmodel eq "gamma" perl "numratecats=$value\\n" 4 Number of rate categories: must be an integer between 1 and 20 perl $p_numratecats4 < 2 || $p_numratecats4 > 20 The number of categories of variable rates (not including the invariant site class if it is being used). Must be set to 1 if ratehetmodel is set to none. Note that runtimes and memory usage scale linearly with this setting. model_codon4 Codon Model The codon models are built with three components: (1) parameters describing the process of individual nucleotide substitutions, (2) equilibrium codon frequencies, and (3) parameters describing the relative rate of nonsynonymous to synonymous substitutions. The nucleotide substitution parameters within the codon models are exactly the same as those possible with standard nucleotide models in GARLI, and are specified with the ratematrix configuration entry. Thus, they can be of the 2rate variety (inferring different rates for transitions and transversions, K2P or HKY-like), the 6rate variety (inferring different rates for all nucleotide pairs, GTR-like) or any other sub-model of GTR. The options for codon frequencies are specified with the statefrequencies configuration entry. The options are to use equal frequencies (not a good option), the frequencies observed in your dataset (termed empirical in GARLI), or the codon frequencies implied by the F1x4 or F3x4 methods (using PAML's terminology). These last two options calculate the codon frequencies as the product of the frequencies of the three nucleotides that make up each codon. In the F1x4 case the nucleotide frequencies are those observed in the dataset across all codon positions, while the F3x4 option uses the nucleotide frequencies observed in the data at each codon position separately. The final component of the codon models is the nonsynonymous to synonymous relative rate parameters (aka dN/dS or omega parameters). The default is to infer a single dN/dS value. Alternatively, a model can be specified that infers a given number of dN/dS categories, with the dN/dS values and proportions falling in each category estimated (ratehetmodel = nonsynonymous). This is the discrete or M3 model in PAML's terminology. From the Author: No stop codons under the chosen genetic code are allowed. These are: standard code (TAG, TAA and TGA); vertebrate mitochondria (TAG, TAA, AGA and AGG); invertebrate mitochondria (TAG and TAA). One might argue that stop codons should just be ignored and treated as missing, but this can be dangerous. Sometimes they will come from a sequencing error, but more often from an alignment problem, an incorrectly chosen genetic code, or a sequence that is not really coding (e.g. an intron). In any case, error should be examined and resolved consciously by the user. One thing to note is that codon models for tree inference require that you align the protein coding sequences along a correct reading frame; (e.g., gaps of 1 or 2 bases will impair the analysis). Maintaining the reading frame makes alignment much easier even if your analysis will be at the nucleotide level. Just running sequences through a sequence alignment program without looking is almost guaranteed to return an alignment that will not work for codon based inference. The other important restriction to note is that GARLI expects the alignment to begin on the first base of a codon. It can't figure out where the reading frame is, so if the alignment starts with a partial codon it needs to be removed or excluded from the alignment. Version 0.96 does allow normal NEXUS exclusions through an assumptions block, so the following would work to exclude the first two bases of an alignment and tell GARLI that the reading frame starts on the third. begin assumptions; exset * myexset = 1 2; end;. c_ratematrix4 garli.conf 12 Codon Rate Matrix (ratematrix) perl $numparts > 3 && $datatype_value4 eq "codon" perl "ratematrix = $value\\n" 2rate 1rate 1rate 2rate 2rate 6rate 6rate fixed fixed custom custom string string This determines the relative rates of nucleotide substitution assumed by the codon model. The options are exactly the same as those allowed under a normal nucleotide model. A codon model with ratematrix = 2rate specifies the standard Goldman and Yang (1994) model, with different substitution rates for transitions and transversions. c_statefrequencies4 garli.conf 12 Codon Frequencies (statefequencies) perl $numparts > 3 && $datatype_value4 eq "codon" perl "statefrequencies = $value\\n" equal equal empirical empirical (+F) f1x4 F1x4 f3x4 F3x4 f3x4 The options are to use equal codon frequencies (not a good option), the frequencies observed in your dataset (termed empirical in GARLI), or the codon frequencies implied by the F1x4 or F3x4 methods (using PAML's terminology). These last two options calculate the codon frequencies as the product of the frequencies of the three nucleotides that make up each codon. In the F1x4 case the nucleotide frequencies are those observed in the dataset across all codon positions, while the F3x4 option uses the nucleotide frequencies observed in the data at each codon position separately. c_ratehetmodel4 garli.conf 12 dN/dS categories (or Omega) (ratehetmodel) perl $numparts > 3 && $datatype_value4 eq "codon" none A single dN/dS parameter (none) nonsynonymous discrete or M3 model (nonsynonymous) none "ratehetmodel = none\\ninvariantsites = none\\nnumratecats = 1\\n" nonsynonymous "ratehetmodel = nonsynonymous\\ninvariantsites = none\\n" none For codon models, the default is to infer a single dN/dS parameter. Alternatively, a model can be specified that infers a given number of dN/dS categories, with the dN/dS values and proportions falling in each category estimated (ratehetmodel = nonsynonymous). This is the discrete or M3 model of Yang et al. (2000). c_numratecats4 Number of dN/dS parameter categories (numratecats) perl $numparts > 3 && $datatype_value4 eq "codon" && $c_ratehetmodel4 eq "nonsynonymous" perl "numratecats = $value\\n" 3 Number of rate categories: must be an integer between 1 and 8 perl $c_numratecats4 < 1 || $c_numratecats4 > 8 12 garli.conf When ratehetmodel = nonsynonymous, this is the number of dN/dS parameter categories. model5 Model Parameters for Partition 5 datatype_value5 The type of data (datatype) perl $numparts > 4 nucleotide nucleotide nucleotide aminoacid amino acid codon-aminoacid codon-aminoacid codon codon nucleotide "datatype = nucleotide\\n" aminoacid "datatype = aminoacid\\n" codon-aminoacid "datatype = codon-aminoacid\\n" codon "datatype = codon\\n" garli.conf 14 The codon-aminoacid datatype means that the data will be supplied as a nucleotide alignment, but will be internally translated and analyzed using an amino acid model. The codon and codon-aminoacid datatypes require nucleotide sequence that is aligned in the correct reading frame. In other words, all gaps in the alignment should be a multiple of 3 in length, and the alignment should start at the first position of a codon. If the alignment has extra columns at the start, middle or end, they should be removed or excluded with a Nexus exset (see the FAQ for an example of exset usage). The correct geneticcode must also be set. geneticcode_value5 Select the Genetic Code (geneticcode) perl $datatype_value5 eq "codon" || $datatype_value5 eq "codon-aminoacid" perl "geneticcode = $value\\n" standard Standard vertmito Vertebrate Mitochondria invertmito Invertebrate Mitochondria standard garli.conf 14 The codon-aminoacid datatype means that the data will be supplied as a nucleotide alignment, but will be internally translated and analyzed using an amino acid model. The codon and codon-aminoacid datatypes require nucleotide sequence that is aligned in the correct reading frame. In other words, all gaps in the alignment should be a multiple of 3 in length, and the alignment should start at the first position of a codon. If the alignment has extra columns at the start, middle or end, they should be removed or excluded with a Nexus exset (see the FAQ for an example of exset usage). The correct geneticcode must also be set. model_nucleotide5 Nucleotide Model JC (Jukes-Cantor model): Rate Matrix = 1 rate, Base Frequencies = equal K2P (Kimura 2-Parameter model): Rate Matrix = 2 rate, Base Frequencies = equal F81 (Felsenstein 1981 model): Rate Matrix = 1 rate, Base Frequencies = estimate HKY (Hasegawa, Kishino and Yano model): Rate Matrix = 2 rate, Base Frequencies = estimate GTR (General Time-Reversible model): Rate Matrix = 6 rate, Base Frequencies = estimate d_ratematrix5 garli.conf Rate Matrix (ratematrix) perl $numparts > 4 && $datatype_value5 eq "nucleotide" 1rate All Rates Equal (1rate) 2rate HKY (2rate) 6rate General time-reversible (6 rate) fixed fixed rate custom_string User Specified 1rate "ratematrix = $value\\n" 2rate "ratematrix = $value\\n" 6rate "ratematrix = $value\\n" fixed "ratematrix = $value\\n" custom_string "ratematrix = ($ACsubrates5 $AGsubrates5 $ATsubrates5 $CGsubrates5 $CTsubrates5 $GTsubrates5)\\n" 6rate garli.conf 14 New in version 0.96, parameters for any submodel of the GTR model may now be estimated. The format for specifying this is very similar to that used in the rclass setting of PAUP*. Within parentheses, six letters are specified, with spaces between them. The six letters represent the rates of substitution between the six pairs of nucleotides, with the order being A-C, A-G, A-T, C-G, C-T and G-T. Letters within the parentheses that are the same mean that a single parameter is shared by multiple nucleotide pairs. For example, ratematrix = (a b a a b a) would specify the HKY 2-rate model (equivalent to ratematrix = 2rate). This entry, ratematrix = (a b c c b a) would specify 3 estimated rates of substitution, with one rate shared by A-C and G-T substitutions, another rate shared by A-G and C-T substitutions, and the final rate shared by A-T and C-G substitutions. ACsubrates5 User specified AC substitution rates (custom ratematrix) perl $numparts > 4 && $datatype_value5 eq "nucleotide" && $d_ratematrix5 eq "custom_string" perl "" AGsubrates5 User specified AG substitution rates (custom ratematrix) perl $numparts > 4 && $datatype_value5 eq "nucleotide" && $d_ratematrix5 eq "custom_string" perl "" ATsubrates5 User specified AT substitution rates (custom ratematrix) perl $numparts > 4 && $datatype_value5 eq "nucleotide" && $d_ratematrix5 eq "custom_string" perl "" CGsubrates5 User specified CG substitution rates (custom ratematrix) perl $numparts > 4 && $datatype_value5 eq "nucleotide" && $d_ratematrix5 eq "custom_string" perl "" CTsubrates5 User specified CT subsitution rates (custom ratematrix) perl $numparts > 4 && $datatype_value5 eq "nucleotide" && $d_ratematrix5 eq "custom_string" perl "" GTsubrates5 User specified GT substitution rates (custom ratematrix) perl $numparts > 4 && $datatype_value5 eq "nucleotide" && $d_ratematrix5 eq "custom_string" perl "" d_statefrequencies5 garli.conf Base Frequencies (statefrequencies) perl $numparts > 4 && $datatype_value5 eq "nucleotide" perl "statefrequencies = $value\\n" equal equal empirical empirical estimate estimate fixed fixed estimate garli.conf 14 d_invariantsites5 garli.conf Proportion of invariant sites (invariantsites) perl $numparts > 4 && $datatype_value5 eq "nucleotide" perl "invariantsites = $value\\n" none none estimate estimate estimate 14 garli.conf Specifies whether a parameter representing the proportion of sites that are unable to change (i.e. have a substitution rate of zero) will be included. This is typically referred to as invariant sites, but would better be termed invariable sites. d_ratehetmodel5 garli.conf The model of rate heterogeneity (ratehetmodel) perl $numparts > 4 && $datatype_value5 eq "nucleotide" perl ($d_ratehetmodel5 eq "none") ? "numratecats = 1\\nratehetmodel = $value\\n" : "numratecats = $d_numratecats5\\nratehetmodel = $value\\n" none Equal Rates For All Sites (none) gamma Gamma Distribution (gamma) gamma garli.conf 14 The model of rate heterogeneity assumed. gammafixed requires that the alpha shape parameter is provided, and a setting of gamma estimates it. d_numratecats5 Number of rate categories (numratecats) perl $numparts > 4 && $datatype_value5 eq "nucleotide" && $d_ratehetmodel5 eq "gamma" perl "numratecats=$value\\n" 4 :Number of rate categories: must be an integer between 1 and 20 perl $d_numratecats5 < 2 || $d_numratecats5 > 20 garli.conf 14 The number of categories of variable rates (not including the invariant site class if it is being used). Must be set to 1 if ratehetmodel is set to none. Note that runtimes and memory usage scale linearly with this setting. model_protein5 Protein Model dayhoff Dayhoff, Schwartz and Orcutt. 1978 jones Jones, Taylor and Thornton (JTT), 1992 WAG Whelan and Goldman, 2001 mtREV Adachi and Hasegawa, 1996 mtmam Yang, Nielsen and Hasegawa. 1998 p_ratematrix5 garli.conf 14 Protein Rate Matrix (ratematrix) perl $numparts > 4 && ($datatype_value5 eq "aminoacid" || $datatype_value5 eq "codon-aminoacid") perl "ratematrix = $value\\n" wag poisson Poisson jones Jones dayhoff Dayhoff wag WAG mtmam mtMAM mtrev mtREV You should use the matrix that gives the best likelihood, and could use a program like PROTTEST (very much like MODELTEST, but for amino acid models) to determine which fits best for your data. Poisson assumes a single rate of substitution between all amino acid pairs, and is a very poor model. p_statefrequencies5 garli.conf 14 Amino Acid Frequencies (statefequencies) perl $numparts > 4 && ($datatype_value5 eq "aminoacid" || $datatype_value5 eq "codon-aminoacid") perl "statefrequencies = $value\\n" equal equal empirical empirical (+F) estimate estimate fixed fixed jones Jones dayhoff Dayhoff wag WAG mtmam mtMAM mtrev mtREV empirical Specifies how the equilibrium state frequencies of the 20 amino acids are treated. The empirical option fixes the frequencies at their observed proportions (when describing a model this is often termed +F). p_invariantsites5 garli.conf 14 Proportion of invariable sites (invariantsites) perl $numparts > 4 && ($datatype_value5 eq "aminoacid" || $datatype_value5 eq "codon-aminoacid") perl "invariantsites = $value\\n" none none estimate estimate estimate Specifies whether a parameter representing the proportion of sites that are unable to change (i.e. have a substitution rate of zero) will be included. This is typically referred to as invariant sites, but would better be termed invariable sites. p_ratehetmodel5 garli.conf 14 Model of rate heterogeneity (ratehetmodel) perl $numparts > 4 && ($datatype_value5 eq "aminoacid" || $datatype_value5 eq "codon-aminoacid") perl ($p_ratehetmodel5 eq "none") ? "numratecats = 1\\nratehetmodel = $value\\n" : "numratecats = $p_numratecats5\\nratehetmodel = $value\\n" none Equal Rates For All Sites (none) gamma Gamma Distribution (gamma) gamma The model of rate heterogeneity assumed. gammafixed requires that the alpha shape parameter is provided, and a setting of gamma estimates it. p_numratecats5 garli.conf 14 Number of rate categories (numratecats; set at no more than 8) perl $numparts > 4 && ($datatype_value5 eq "aminoacid" || $datatype_value5 eq "codon-aminoacid") && $p_ratehetmodel eq "gamma" perl "numratecats=$value\\n" 4 Number of rate categories: must be an integer between 1 and 20 perl $p_numratecats5 < 2 || $p_numratecats5 > 20 The number of categories of variable rates (not including the invariant site class if it is being used). Must be set to 1 if ratehetmodel is set to none. Note that runtimes and memory usage scale linearly with this setting. model_codon5 Codon Model The codon models are built with three components: (1) parameters describing the process of individual nucleotide substitutions, (2) equilibrium codon frequencies, and (3) parameters describing the relative rate of nonsynonymous to synonymous substitutions. The nucleotide substitution parameters within the codon models are exactly the same as those possible with standard nucleotide models in GARLI, and are specified with the ratematrix configuration entry. Thus, they can be of the 2rate variety (inferring different rates for transitions and transversions, K2P or HKY-like), the 6rate variety (inferring different rates for all nucleotide pairs, GTR-like) or any other sub-model of GTR. The options for codon frequencies are specified with the statefrequencies configuration entry. The options are to use equal frequencies (not a good option), the frequencies observed in your dataset (termed empirical in GARLI), or the codon frequencies implied by the F1x4 or F3x4 methods (using PAML's terminology). These last two options calculate the codon frequencies as the product of the frequencies of the three nucleotides that make up each codon. In the F1x4 case the nucleotide frequencies are those observed in the dataset across all codon positions, while the F3x4 option uses the nucleotide frequencies observed in the data at each codon position separately. The final component of the codon models is the nonsynonymous to synonymous relative rate parameters (aka dN/dS or omega parameters). The default is to infer a single dN/dS value. Alternatively, a model can be specified that infers a given number of dN/dS categories, with the dN/dS values and proportions falling in each category estimated (ratehetmodel = nonsynonymous). This is the discrete or M3 model in PAML's terminology. From the Author: No stop codons under the chosen genetic code are allowed. These are: standard code (TAG, TAA and TGA); vertebrate mitochondria (TAG, TAA, AGA and AGG); invertebrate mitochondria (TAG and TAA). One might argue that stop codons should just be ignored and treated as missing, but this can be dangerous. Sometimes they will come from a sequencing error, but more often from an alignment problem, an incorrectly chosen genetic code, or a sequence that is not really coding (e.g. an intron). In any case, error should be examined and resolved consciously by the user. One thing to note is that codon models for tree inference require that you align the protein coding sequences along a correct reading frame; (e.g., gaps of 1 or 2 bases will impair the analysis). Maintaining the reading frame makes alignment much easier even if your analysis will be at the nucleotide level. Just running sequences through a sequence alignment program without looking is almost guaranteed to return an alignment that will not work for codon based inference. The other important restriction to note is that GARLI expects the alignment to begin on the first base of a codon. It can't figure out where the reading frame is, so if the alignment starts with a partial codon it needs to be removed or excluded from the alignment. Version 0.96 does allow normal NEXUS exclusions through an assumptions block, so the following would work to exclude the first two bases of an alignment and tell GARLI that the reading frame starts on the third. begin assumptions; exset * myexset = 1 2; end;. c_ratematrix5 garli.conf 14 Codon Rate Matrix (ratematrix) perl $numparts > 4 && $datatype_value5 eq "codon" perl "ratematrix = $value\\n" 2rate 1rate 1rate 2rate 2rate 6rate 6rate fixed fixed custom custom string string This determines the relative rates of nucleotide substitution assumed by the codon model. The options are exactly the same as those allowed under a normal nucleotide model. A codon model with ratematrix = 2rate specifies the standard Goldman and Yang (1994) model, with different substitution rates for transitions and transversions. c_statefrequencies5 garli.conf 14 Codon Frequencies (statefequencies) perl $numparts > 4 && $datatype_value5 eq "codon" perl "statefrequencies = $value\\n" equal equal empirical empirical (+F) f1x4 F1x4 f3x4 F3x4 f3x4 The options are to use equal codon frequencies (not a good option), the frequencies observed in your dataset (termed empirical in GARLI), or the codon frequencies implied by the F1x4 or F3x4 methods (using PAML's terminology). These last two options calculate the codon frequencies as the product of the frequencies of the three nucleotides that make up each codon. In the F1x4 case the nucleotide frequencies are those observed in the dataset across all codon positions, while the F3x4 option uses the nucleotide frequencies observed in the data at each codon position separately. c_ratehetmodel5 garli.conf 14 dN/dS categories (or Omega) (ratehetmodel) perl $numparts > 4 && $datatype_value5 eq "codon" none A single dN/dS parameter (none) nonsynonymous discrete or M3 model (nonsynonymous) none "ratehetmodel = none\\ninvariantsites = none\\nnumratecats = 1\\n" nonsynonymous "ratehetmodel = nonsynonymous\\ninvariantsites = none\\n" none For codon models, the default is to infer a single dN/dS parameter. Alternatively, a model can be specified that infers a given number of dN/dS categories, with the dN/dS values and proportions falling in each category estimated (ratehetmodel = nonsynonymous). This is the discrete or M3 model of Yang et al. (2000). c_numratecats5 Number of dN/dS parameter categories (numratecats) perl $numparts > 4 && $datatype_value5 eq "codon" && $c_ratehetmodel5 eq "nonsynonymous" perl "numratecats = $value\\n" 3 Number of rate categories: must be an integer between 1 and 8 perl $c_numratecats5 < 1 || $c_numratecats5 > 8 14 garli.conf When ratehetmodel = nonsynonymous, this is the number of dN/dS parameter categories. model_trees Run Configuration streefname_choose Specify where the starting tree topology comes from (streefname) stepwise random random stepwise stepwise upload upload random "streefname = random\\n" stepwise "streefname = stepwise\\n" upload "streefname = starting.txt\\n" garli.conf 2 With this selection, you must upload a starting tree topology file when you use the garli.conf file produced here to configure the run using the Garli 2.0 on TG interface perl $user_conffile && $user_conffile_there && $streefname_choose eq "upload" streefname Specifies where the starting tree topology and/or model parameters will come from. The tree topology may be a completely random topology (constraints will be enforced), a tree provided by the user in a file, or a tree generated by the program using a fast ML stepwise-addition algorithm (see attachmentspertaxon below). The author recommends stepwise over random. This will give it a much better starting point; on large datasets this can both reduce runtimes and improve results.Starting or fixed model parameter values may also be provided in the specified file, with or without a tree topology. Some notes on starting trees/models: Nexus starting trees are allowed. Specified starting trees may have polytomies, which will be arbitrarily resolved before the run begins. Allowed Starting tree formats: Plain newick tree string (with taxon numbers or names, with or without branch lengths) or NEXUS trees block. The trees block can appear in the same file as a NEXUS data or characters block that contains the alignment, but it must specfied a second time in this box. If multiple trees appear in the specified file and multiple search replicates are specified (see searchreps setting), then the first tree is used in the first replicate, the second in the second replicate, etc. attachments_val Specify the number of attachment branches evaluated for each taxon (attachmentspertaxon) perl $streefname_choose eq "stepwise" 50 perl "attachmentspertaxon=$value\\n" garli.conf 2 New Param for V 0.96. The number of attachment branches evaluated for each taxon to be added to the tree during the creation of an ML stepwise-addition starting tree. Briefly, stepwise addition is an algorithm used to make a tree, and involves adding taxa in a random order to a growing tree. For each taxon to be added, a number of randomly chosen attachment branches are tried and scored, and then the best scoring one is chosen as the location of that taxon. The attachmentspertaxon setting controls how many attachment points are evaluated for each taxon to be added. A value of one is equivalent to a completely random tree (only one randomly chosen location is evaluated). A value of greater than 2 times the number of taxa in the dataset means that all attachment points will be evaluated for each taxon, and will result in very good starting trees (but may take a while on large datasets). Even fairly small values (less than 10) can result in starting trees that are much, much better than random, but still fairly different from one another. searchreps_value Specify the number of independent search replicates to perform during a program execution.(searchreps) 2 perl ($bootstrapreps > 1) ? "searchreps=$value\\n" : "searchreps=1\\n" garli.conf 2 The value for this parameter cannot be less than 1 perl $searchreps_value < 1 You must specify multiple searchreps and/or multiple bootstrapreps to do a parallel run on teragrid. perl $searchreps_value < 2 && $bootstrapreps < 2 Sorry, the number of searchreps must be no more than 120. perl $searchreps_value > 120 Please enter an integer value for search repetitions perl !defined $searchreps_value The number of independent search replicates to perform during a program execution. You should always either do multiple search replicates or multiple program executions with any dataset to get a feel for whether you are getting consistent results, which suggests that the program is doing a decent job of searching. Note that if this is greater than 1 and you are performing a bootstrap analysis, this is the number of search replicates to be done per bootstrap replicate. That can increase the chance of finding the best tree per bootstrap replicate, but will also increase bootstrap runtimes enormously. When you specify multiple searchreps or multiple bootstraps, we will automatically run garli multiple times in parallel. bootstrapreps Bootstrap Repetitions (-bootstrapreps) perl !$inferinternalstateprobs_g 0 Bootstrap Repititions must be 0 or an integer 2 or greater for parallel runs on teragrid. perl $value < 0 || $value == 1 Sorry, the number of bootstrapreps must be no more than 100. perl $bootstrapreps > 100 Sorry, the number of bootstrap reps times the number of searchreps must be no more than 100. Please decrease the number of searchreps, and/or the number bootstrapreps to meet this criterion. You may make addtional identical runs, if you require more bootstrapreps. perl $searchreps_value * $bootstrapreps > 100 The number of bootstrap reps to perform. If the value entered is 0,normal searching will be performed. If a value greater than 0 is entered, normal searching will not be performed. The resulting bootstrap trees (one per rep) will be output to a file named ofprefix.boot.tre. To obtain the bootstrap proportions they will then need to be read into PAUP* or a similar program to obtain a majority rule consensus. Note that it is probably safe to reduce the strictness of the termination conditions during bootstrapping (perhaps halve genthreshfortopoterm), which will greatly speed up the bootstrapping process with negligible effects on the results. When multiple bootstrapreps or multiple searchreps are specified we will automatically run garli multiple times in parallel. outgroup_tax garli.conf 2 Outgroup taxa numbers, separated by spaces (outgroup) perl "outgroup = $value\\n" The outgroup option allow for orienting tree topologies in a consistent way when they are written to file. Note that this has NO effect whatsoever on the actual inference and the specified outgroup is NOT constrained to be present in the inferred trees. If multiple outgroup taxa are specified and they do not form a monophyletic group, this setting will be ignored. If you specify a single outgroup taxon it will always be present, and the tree will always be consistently oriented. To specify an outgroup consisting of taxa 1, 3 and 5 the format is this: outgroup = 1 3 5 collapsebranches_g Collapse minimum length branches (effectively zero length) branch upon output of the final tree 0 collapsebranches garli.conf 2 perl "collapsebranches = $collapsebranches_g\\n" Collapse branches tells the program to collapse minimum length branches (effectively zero length) branch upon output of the final trees. Otherwise the final trees are always fully bifurcating, even when returning a polytomy makes more sense. For some datasets this can make a big difference, because final trees may in fact be identical with those branches collapsed, but they will appear different if they are compared on the basis of the topology alone (for example, when calculating tree to tree distances). If visualized with the branches proportional to their lengths the trees will look identical because the tiny branches will be indistinguishable from a polytomy. This feature can be particularly important in the case of bootstrapping, where you don't really want branches that effectively don't exist (and are an arbitrary resolution of a polytomy) to be counted in the support values. The only downside of this setting is that GARLI's test at the end of a run for whether the trees from each replicates are identical may be wrong if branches are collapsed. constraintfile 2 I want to use a Constraint File (constraintfile; Newick format) garli.conf perl ($constraintfile) ? "constraintfile = constraint.txt\\n" : "constraintfile = none\\n" 0 With this selection, you must upload a constraint file to use the garli.conf file produced here to using the Garli 2.0 on TG interface perl $constraintfile The constraint file is in Newick format, and contains any topology constraint specifications, or none if there are no constraints. With Version 0.96, backbone constraints can be uploaded. A backbone constraint is the same as any other constraint file, but not all taxa need be represented. Format: Consider a dataset of 8 taxa, in which your constraint consists of grouping taxa 1, 3 and 5. You may specify either positive constraints (inferred tree MUST contain constrained group) or negative constraints (also called converse constraints, inferred tree CANNOT contain constrained group). These are specified with either a + or a - at the beginning of the constraint specification, for positive and negative constraints, respectively. For a positive constraint on a grouping of taxa 1, 3 and 5: +((1,3,5), 2, 4, 6, 7, 8); For a negative constraint on a grouping on taxa 1, 3 and 5: -((1,3,5), 2, 4, 6, 7, 8); (Note that there are many other equivalent parenthetical representations of this constraint.) GARLI also accepts another constraint format that may be easier to use in some cases. This involves specifying a single branch to be constrained with a string of * (asterisk) and . (period) characters, with one character per taxon. Each taxon specified with a * falls on one side of the constrained branch, and all those specified with a . fall on the other. This should be familiar to anyone who has looked at PAUP* bootstrap output. With this format, a positive constraint on a grouping of taxa 1, 3 and 5 would look like this: +*.*.*... or alternatively like this: +.*.*.*** With this format each line only designates a single branch, so multiple constrained branches may be specified as multiple lines in the file. model_initialization Initialization model_initialization_hidden garli.conf 2 perl "refinestart = $refinestart\\n" . "randseed = $randseed\\n" refinestart Perform Initial Rough Optimization (refinestart) 1 Specifies whether some initial rough optimization is performed on the starting branch lengths and alpha parameter. This is always recommended. randseed Random Seed ( -1 means it will be chosen for you) -1 The random number seed used by the random number generator. Specify -1 to have a seed chosen for you. Specifying the same seed number in multiple runs will result in exactly identical runs, if all other parameters are also identical. algorithm Genetic Algorithm algorithm_population Population poplulation_hidden garli.conf 92 perl "selectionintensity = $selectionintensity\\n" . "nindivs = $nindivs\\n" . "holdover = $holdover\\n" selectionintensity Selection Intensity (0.01 to 5.0) (selectionintensity) 0.5 Selection Intensity must be between 0.01 - 5.0 perl $selectionintensity < 0.01 || $selectionintensity > 5.0 Controls the strength of selection, with larger numbers denoting stronger selection. The relative probability of reproduction of two individuals depends on the difference in their log likelihoods (delta lnL) and is formulated very similarly to the procedure of calculating Akaike weights. The relative probability of reproduction of the less fit individual is equal to: In general this setting does not seem to have much of an effect on the progress of a run. In theory higher values should cause scores to increase more quickly, but make the search more likely to be entrapped in a local optimum. The following table gives the relative probabilities of reproduction for different values of the selection intensity when the difference in log likelihood is 1.0 Selection intensity Ratio of probabilities of reproduction 0.05 0.95:1.0 0.1 0.90:1.0 0.25 0.78:1.0 0.5 0.61:1.0 0.75 0.47:1.0 1 0.37:1.0 2 0.14:1.0 nindivs Number of Individuals (nindivs 2 to 100) 4 Number of individuals must be between 2 - 100 perl $nindivs < 2 || $nindivs > 100 The number of individuals in the population. This may be increased, but generally seems to slow the rate of score increase. holdover 1 algorithm_brlen Branch-length Optimization brlen_hidden garli.conf 92 perl "startoptprec = $startoptprec\\n" . "minoptprec = $minoptprec\\n" . "numberofprecreductions = $numberofprecreductions\\n" startoptprec Starting Precision (startoptprec: 0.005 - 5.0) 0.5 Starting Precision must be between 0.005 - 5.0 perl $startoptprec < 0.005 || $startoptprec > 5.0 minoptprec Minimum Precision (minoptprec: 0.001 - 0.01) 0.01 Minimum Precision must be between 0.001 - 0.01 perl $minoptprec < 0.001 || $minoptprec > 0.01 numberofprecreductions Number of Precision Reductions (0 - 100) 20 Number of Precision Reductions must be between 0 - 100 perl $minoptprec < 0 || $minoptprec > 100 Specify the number of steps that it will take for the optimization precision to decrease from startoptprec to minoptprec. In version 0.95, the reduction from startoptprec to minoptprec is linear, rather than geometric. algorithm_mutation_prior_weighting Mutation Prior Weighting prior_weighting_hidden garli.conf 92 perl "modweight = $modweight\\n" . "brlenweight = $brlenweight\\n" . "topoweight = $topoweight\\n" . "randnniweight = $randnniweight\\n" . "randsprweight = $randsprweight\\n" . "limsprweight = $limsprweight\\n" modweight Model Mutations (modweight) 0.05 Model Mutations must be 0 or greater. perl $modweight < 0 The prior weight assigned to the class of model mutations. Note that setting this at 0.0 fixes the model during the run. brlenweight Branch-length Mutations (brlenweight) 0.2 Branch-length Mutations must be 0 or greater. perl $brlenweight < 0 The prior weight assigned to branch-length mutations. topoweight garli.conf 92 All Topology Mutations (topoweight) 1.0 :All Topology Mutations: must be 0 or greater. perl $topoweight < 0 The prior weight assigned to the class of topology mutations (NNI, SPR and limSPR). randnniweight NNI Mutations (randnniweight) 0.1 NNI Mutations must be 0 or greater. perl $randnniweight < 0 The prior weight assigned to NNI mutations. randsprweight SPR Mutations (randsprweight) 0.3 SPR Mutations must be 0 or greater. perl $randsprweight < 0 randsprweight (0 to infinity, 0.3) -The prior weight assigned to random SPR mutations. For very large datasets it is often best to set this to 0.0, as random SPR mutations essentially never result in score increases. limsprweight Limited SPR Mutations (limsprweight) 0.6 Limited SPR Mutations must be 0 or greater. perl $limsprweight < 0 The prior weight assigned to SPR mutations with the reconnection branch limited to being a maximum of limsprrange branches away from where the branch was detached. algorithm_mutation_details Mutation Details mutation_details_hidden garli.conf 92 perl "limsprrange= $limsprrange\\n" . "uniqueswapbias = $uniqueswapbias\\n" . "distanceswapbias = $distanceswapbias\\n" limsprrange Max Limited SPR Branch Movement (limsprrange) 6 Limited SPR Branch Movement must be 0 or greater. perl $limsprrange < 0 The maximum number of branches away from its original location that a branch may be reattached during a limited SPR move. Setting this too high (> 10) can seriously degrade performance. uniqueswapbias Unique Swap Bias (uniqueswapbias) 0.1 Unique Swap Bias must be between 0.01 - 1.0 perl $uniqueswapbias < 0.01 || $uniqueswapbias > 1.0 distanceswapbias Distance Swap Bias (distanceswapbias) 1.0 general_logs Logs saveevery_g Save best tree with interval (saveevery) 100 Save best tree with interval must be greater than 1 perl $value < 1 saveevery garli.conf 2 perl "saveevery = $saveevery_g\\n" outputcurrentbesttopology Output current best tree at "savevery" interval (outputcurrentbesttopology) garli.conf perl !$user_conffile 2 perl ($value) ? "outputcurrentbesttopology = 1\\n" : "outputcurrentbesttopology = 0\\n" logevery_g Save best score with interval (logevery) 10 Save best score with interval must be greater than 1 perl $value < 1 The frequency with which the best score is written to the log file. logevery garli.conf 2 perl "logevery = $logevery_g\\n" outputeachbettertopology_g Save each improved topology (outputeachbettertopology; can result in a very large file) 0 If true, each new topology encountered with a better score than the previous best is written to file. In some cases this can result in really big files, possibly hundreds of MB, especially for random starting topologies on large datasets. Note that this file is interesting to get an idea of how the topology changed as the searches progressed, but the collection of trees should NOT be interpreted in any meaningful way. This option is not available while bootstrapping. outputeachbettertopology garli.conf 2 perl "outputeachbettertopology = $outputeachbettertopology_g\\n" inferinternalstateprobs_g Output state probabilities of internal nodes (inferinternalstateprobs) 0 perl $bootstrapreps eq 0 inferinternalstateprobs garli.conf 92 perl "inferinternalstateprobs = $inferinternalstateprobs_g\\n" Use this flag to have GARLI infer the marginal posterior probability of each character at each internal node. This is done at the very end of the run, just before termination. The results are output to a file named ofprefix.internalstates.log. outputphyliptree_g Output PHYLIP-format tree (outputphyliptree) 0 outputphyliptree garli.conf 2 perl "outputphyliptree = $outputphyliptree_g\\n" outputmostlyuselessfiles_g Output files of questionable utility 0 outputmostlyuselessfiles garli.conf 2 perl "outputmostlyuselessfiles = $outputmostlyuselessfiles_g\\n" Whether to output three files of little general interest: the fate, problog, and swaplog files. The fate file shows the parentage, mutation types and scores of every individual in the population during the entire search. The problog shows how the proportions of the different mutation types changed over the course of the run. The swaplog shows the number of unique swaps and the number of total swaps on the current best tree over the course of the run. general_run Run Termination hidden_group2 garli.conf 2 perl "enforcetermconditions = $enforcetermconditions\\n" . "genthreshfortopoterm = $genthreshfortopoterm\\n" . "significanttopochange = $significanttopochange\\n" . "scorethreshforterm = $scorethreshforterm\\n" hidden_group4 garli.conf 92 perl "stopgen = $stopgen\\n" . "stoptime = $stoptime\\n" . "resampleproportion = $resampleproportion\\n" hidden_group4_bootstrap garli.conf 92 perl ($bootstrapreps > 1) ? "bootstrapreps=1\\n" : "bootstrapreps=$bootstrapreps\\n" enforcetermconditions Automatically terminate run (enforcetermconditions; recommended) 1 genthreshfortopoterm perl $enforcetermconditions Generations without improving topology (genthreshfortopoterm) 20000 Generations without improving topology must be a positive integer perl $value < 0 This specifies the first part of the termination condition. When no new significantly better scoring topology see significanttopochange below) has been encountered in greater than this number of generations, this condition is met. Increasing this parameter may improve the lnL scores obtained (especially on large datasets), but will also increase runtimes. significanttopochange perl $enforcetermconditions lnL increase for significantly better topology (significanttopochange) 0.01 lnL increase for significantly better topology must be a positive number perl $value < 0 The lnL increase required for a new topology to be considered significant as far as the termination condition is concerned. It probably doesn't need to be played with, but you might try increasing it slightly if your runs reach a stable score and then take a very long time to terminate due to very minor changes in topology. scorethreshforterm perl $enforcetermconditions Score improvement threshold (scorethreshforterm) 0.05 :Score improvement threshold: must be a positive number. perl $value < 0 The second part of the termination condition. When the total improvement in score over the last intervallength x intervalstostore generations (default is 500 generations, see below) is less than this value, this condition is met. This does not usually need to be changed. stopgen Limit generations to maximum of (stopgen) 214783646 :Limit generations to maximum of: must be a positive number perl $value < 1 The maximum number of generations to run. Note that this supersedes the automated stopping criterion (see enforcetermconditions above), and should therefore be set to a very large value if automatic termination is desired. stoptime Limit run time to maximum of (stoptime, in seconds) 214783646 :Limit run time to maximum of: must be a positive number perl $value < 1 The maximum number of seconds for the run to continue. Note that this supersedes the automated stopping criterion (see enforcetermconditions above), and should therefore be set to a very large value if automatic termination is desired. resampleproportion Resampling where the pseudoreplicate datasets have a different number of alignment columns than the real data (resampleproportion) perl $bootstrapreps > 0 1.0 Resample proportion must be a positive number less than 10 perl $value < 0 || $value > 10 When bootstrapreps is greater than 0, this setting allows for bootstrap-like resampling, but with the pseudoreplicate datasets having a different number of alignment columns than the real data. Setting values less than 1.0 is akin to jackknifing writecheckpoints garli.conf 2 Write Checkpoints (writecheckpoints) perl "writecheckpoints = $vdef\\n" 0 restart garli.conf 2 Restart (restart) perl "restart = $vdef\\n" 0 holdoverpenalty garli.conf 92 Holdover Penalty (holdoverpenalty) perl "holdoverpenalty = $vdef\\n" 0 treerejectionthreshold garli.conf 92 treerejectionthreshold perl "treerejectionthreshold = $vdef\\n" 50.0 intervallength garli.conf 92 intervallength perl "intervallength = $vdef\\n" 100 intervalstostore garli.conf 92 intervalstostore perl "intervalstostore = $vdef\\n" 5 meanbrlenmuts garli.conf 92 Mean Branch-length mutations (1 - # taxa) perl "meanbrlenmuts = $vdef\\n" 5 gammashapebrlen garli.conf 92 gammashapebrlen perl "gammashapebrlen = $vdef\\n" 1000 gammashapemodel garli.conf 92 gammashapemodel perl "gammashapemodel = $vdef\\n" 1000