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* seqfile = mtCDNApri.nuc * sequence data filename
seqfile = mtCDNApri.aa * sequence data filename
treefile = mtCDNApri.trees * tree file name
outfile = mlc * main result file name
noisy = 3 * 0,1,2,3,9: how much rubbish on the screen
verbose = 1 * 0: concise; 1: detailed, 2: too much
runmode = 0 * 0: user tree; 1: semi-automatic; 2: automatic
* 3: StepwiseAddition; (4,5):PerturbationNNI; -2: pairwise
seqtype = 2 * 1:codons; 2:AAs; 3:codons-->AAs
CodonFreq = 0 * 0:1/61 each, 1:F1X4, 2:F3X4, 3:codon table
* 4:F1x4MG, 5:F3x4MG, 6:FMutSel0, 7:FMutSel
* estFreq = 0
* hkyREV = 0 * 0: HKY-like; 1: GTR(REV)-like
* ndata = 1 * number of data sets or loci
* bootstrap = 0 * generate bootstrap data sets
model = 5
* models for codons:
* 0:one, 1:b, 2:2 or more dN/dS ratios for branches, 6:FromCodon
* models for AAs or codon-translated AAs:
* 0:poisson, 1:proportional, 2:Empirical, 3:Empirical+F
* 6:FromCodon, 7:AAClasses, 8:REVaa_0, 9:REVaa(nr=189)
NSsites = 0 * 23 24 25 26 * 23 24 25 26 * 0:one w; 1:NearlyNeutral; 2:PositiveSelection; 3:discrete;
* 4:freqs; 5:gamma; 6:2gamma; 7:beta; 8:beta&w+; 9:betaγ
* 10:beta&gamma+1; 11:beta&normal>1; 12:0&2normal>1;
* 13:3normal>0;
* 22:M2a_Old(M2a_rel);
* 23:Tgamma; 24:Tinvgamma; 25:Tgamma+1; 26:Tinvgamma+1.
clock = 0 * 0:no clock, 1:global clock; 2:local clock
aaDist = 0 * 0:equal, +:geometric; -:linear, 1-6:G1974,Miyata,c,p,v,a
aaRatefile = jones.dat * for aa seqs under model = 3 (empirical+F)
* dayhoff.dat, jones.dat, wag.dat, mtmam.dat, or your own
icode = 1 * 0:universal code; 1:mammalian mt; 2-10:see below
Mgene = 0
* codon: 0:rates, 1:separate; 2:diff pi, 3:diff kappa, 4:all diff
* AA: 0:rates, 1:separate
* NShmm = 0 * 1: hidden Markov model
fix_kappa = 0 * 1: kappa fixed, 0: kappa to be estimated
kappa = 3 * initial or fixed kappa
fix_omega = 0 * 1: omega or omega_1 fixed, 0: estimate
omega = 1.5 * initial or fIf yoixed omega, for codons or codon-based AAs
fix_alpha = 1 * 0: estimate gamma shape parameter; 1: fix it at alpha
alpha = 0. * initial or fixed alpha, 0:infinity (constant rate)
Malpha = 0 * different alphas for genes
ncatG = 10 * # of categories in dG of NSsites models
getSE = 1 * 0: don't want them, 1: want S.E.s of estimates
RateAncestor = 1 * (0,1,2): rates (alpha>0) or ancestral states (1 or 2)
Small_Diff = 1e-8
* cleandata = 1 * remove sites with ambiguity data (1:yes, 0:no)?
* fix_blength = 1 * 0: ignore, -1: random, 1: initial, 2: fixed
* method = 0 * Optimization method 0: simultaneous; 1: one branch a time
* Genetic codes: 0:universal, 1:mammalian mt., 2:yeast mt., 3:mold mt.,
* 4: invertebrate mt., 5: ciliate nuclear, 6: echinoderm mt.,
* 7: euplotid mt., 8: alternative yeast nu. 9: ascidian mt.,
* 10: blepharisma nu., 11: Yang's regularized code
* These codes correspond to transl_table 1 to 11 of GenBank.
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