File: model2.ctl

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python-biopython 1.68%2Bdfsg-3
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      seqfile = PAML/alignment.phylip
     treefile = PAML/species.tree

      outfile = temp.out       * main result file
        noisy = 0   * 0,1,2,3: how much rubbish on the screen
      verbose = 0   * 1: detailed output, 0: concise output
      runmode = 0   * 0: user tree;  1: semi-automatic;  2: automatic
                    * 3: StepwiseAddition; (4,5):PerturbationNNI

        model = 2   * 0:JC69, 1:K80, 2:F81, 3:F84, 4:HKY85
                    * 5:T92, 6:TN93, 7:REV, 8:UNREST, 9:REVu; 10:UNRESTu

        Mgene = 1   * 0:rates, 1:separate; 2:diff pi, 3:diff kapa, 4:all diff

*        ndata = 100
        clock = 0   * 0:no clock, 1:clock; 2:local clock; 3:CombinedAnalysis
    fix_kappa = 0   * 0: estimate kappa; 1: fix kappa at value below
        kappa = 5  * initial or fixed kappa

    fix_alpha = 0   * 0: estimate alpha; 1: fix alpha at value below
        alpha = 0.5   * initial or fixed alpha, 0:infinity (constant rate)
       Malpha = 0   * 1: different alpha's for genes, 0: one alpha
        ncatG = 5   * # of categories in the dG, AdG, or nparK models of rates
       fix_rho = 1
          rho = 0
	nparK = 0   * rate-class models. 1:rK, 2:rK&fK, 3:rK&MK(1/K), 4:rK&MK

        nhomo = 0   * 0 & 1: homogeneous, 2: kappa for branches, 3: N1, 4: N2
        getSE = 0   * 0: don't want them, 1: want S.E.s of estimates
 RateAncestor = 0   * (0,1,2): rates (alpha>0) or ancestral states

   Small_Diff = 7e-6
    cleandata = 1  * remove sites with ambiguity data (1:yes, 0:no)?
*        icode = 0  * (with RateAncestor=1. try "GC" in data,model=4,Mgene=4)
*  fix_blength = -1  * 0: ignore, -1: random, 1: initial, 2: fixed
       method = 0  * Optimization method 0: simultaneous; 1: one branch a time