cgprecision

Fixes the nuber of printed digits when CarthaGene outputs estimated distances. Useful if you want to see precise distance estimations maps built from a very large number of individuals (10,000 or more). The convergence of the EM algorithm must be simultaneously tuned to smaller tolerance using cgtolerance.

Synopsis:

The cgprecision command is invoked as either:

• cgprecision Options
• cgprecision precision

Description:

The cgprecision command sets the number of digits printed after the decimal point when estimated parameters are printed in maps.

Arguments:

• Options : -u to obtain the synopsys of the normal use, -h to print a one line description, -H to print a short help.
• precision: the number of digits to print.

Example:

   CarthaGene version 1.2-LKH, Copyright (c) 1997-2010 (INRA).

   CarthaGene comes with ABSOLUTELY NO WARRANTY.
   CarthaGene is free software. You are welcome to redistribute it,
   under certain conditions. See the License file for information.

Type 'help' for help.

CG> dsload Data/rh1.cg
{1 haploid RH 13 118 /home/tschiex/Dev/carthagene/doc/user/exemple/Data/rh1...
CG> cgtolerance 0.00001 0.0001

CG> cgprecision 5

CG> sem

Map -1 : log10-likelihood =  -286.90
-------:
 Set : Marker List ...
   1 : G36 MS5 MS6 MS7 MS9 MS8 MS1 G39 MS3 G37 MS15 G40 MS4

CG> bestprintd

Map  0 : log10-likelihood =  -286.90, log-e-likelihood =  -660.62
-------:

Data Set Number  1 :

               Markers Distance      Cumulative   Theta        2pt
 Pos  Id name                                   (%%age)       LOD

  1   1  G36          97.78057 cR    0.00000 cR     62.4 %       3.2
  2   2  MS5          57.76337 cR    97.78057 cR     43.9 %       7.4
  3   3  MS6          33.08984 cR    155.54394 cR     28.2 %      12.8
  4   4  MS7          76.94695 cR    188.63378 cR     53.7 %       5.4
  5   5  MS9          16.88066 cR    265.58073 cR     15.5 %      18.5
  6   6  MS8          184.14327 cR    282.46139 cR     84.1 %       0.5
  7   7  MS1          85.61036 cR    466.60466 cR     57.5 %       3.8
  8   8  G39          46.88826 cR    552.21502 cR     37.4 %       9.7
  9   9  MS3          29.07694 cR    599.10327 cR     25.2 %      13.3
 10  10  G37          236.70602 cR    628.18022 cR     90.6 %       0.2
 11  11 MS15          760.09025 cR    864.88624 cR    100.0 %      -0.0
 12  12  G40          41.55418 cR    1624.97648 cR     34.0 %      10.5
 13  13  MS4          ---------
                      1666.5 cR


       13 markers, log10-likelihood =  -286.90
                   log-e-likelihood =  -660.62
                   retention proba. =     0.25
0
CG>