Subsections


bestprintd

Precisely describes the best map in the heap.

Synopsis:

The bestprintd command is invoked as:

Description:

The bestprintd command prints an extensive description of the best map in the heap. For each data-set for which parameters have been estimated (merged using mergor), the map is described by successively giving, line per line:
  1. the position of the marker in the overall map for this data set
  2. the numerical Id of the marker
  3. the name of the marker (truncated to a mxaimum number of characters)
  4. the Haldane distance to the next marker (if any). Rays are used for RH data.
  5. The cumulative distance of the marker from the beginning of the map (Haldane/Ray).
  6. For genetic data, the Kosambi distance from the next marker (if any)
  7. the estimated recombination ratio/breakage with the next marker
  8. the two-points LOD with the next marker
Then the length of the map, the number of markers and the $\log_{10}$ and natural logarithm of the likelihood of the map are displayed.

Arguments:

none.

Returns:

nothing.

Example:

CG> dsload Data/bc.cg
{1 f2 backcross 20 208 /home/tschiex/Dev/carthagene/doc/user/exemple/Data/b...
CG> sem

Map -1 : log10-likelihood =  -291.76
-------:
 Set : Marker List ...
   1 : MS1 MS2 MS3 MS4 MS5 MS6 MS7 MS8 MS9 MS10 MS11 MS12 MS13 MS14 MS15 MS...

CG> flips 6 0 1
...
CG> bestprintd

Map  9 : log10-likelihood =  -291.76, log-e-likelihood =  -671.79
-------:

Data Set Number  1 :

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

  1   1  MS1          19.5 cM      0.0 cM     16.8 cM    16.2 %%    15.7
  2   2  MS2           0.6 cM     19.5 cM      0.6 cM     0.6 %%    47.6
  3   3  MS3           5.8 cM     20.1 cM      5.5 cM     5.5 %%    35.1
  4   4  MS4           3.7 cM     25.9 cM      3.6 cM     3.5 %%    21.1
  5   5  MS5           3.7 cM     29.6 cM      3.6 cM     3.6 %%    15.4
  6   6  MS6           1.6 cM     33.3 cM      1.6 cM     1.6 %%    17.3
  7   7  MS7           6.7 cM     34.9 cM      6.3 cM     6.3 %%    35.1
  8   8  MS8           2.2 cM     41.6 cM      2.2 cM     2.2 %%    40.8
  9   9  MS9           3.0 cM     43.8 cM      2.9 cM     2.9 %%     7.2
 10  10 MS10           5.4 cM     46.8 cM      5.1 cM     5.1 %%     3.6
 11  11 MS11           8.6 cM     52.2 cM      7.9 cM     7.9 %%    11.9
 12  13 MS13           0.0 cM     60.7 cM      0.0 cM     0.0 %%    18.7
 13  12 MS12           0.0 cM     60.7 cM      0.0 cM     0.0 %%     3.6
 14  14 MS14           5.8 cM     60.7 cM      5.5 cM     5.5 %%     0.0
 15  15 MS15           4.6 cM     66.6 cM      4.4 cM     4.4 %%    26.6
 16  16 MS16          26.1 cM     71.1 cM     21.6 cM    20.3 %%     6.3
 17  17 MS17           0.0 cM     97.2 cM      0.0 cM     0.0 %%    16.0
 18  18 MS18           4.9 cM     97.2 cM      4.7 cM     4.6 %%    27.1
 19  19 MS19           3.0 cM    102.1 cM      2.9 cM     2.9 %%    34.8
 20  20 MS20        ----------              ----------
                     105.1 cM                 95.0 cM


       20 markers, log10-likelihood =  -291.76
                   log-e-likelihood =  -671.79
9

See also:

Thomas Schiex 2009-10-27