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11.6 Running lm_schnell example and sample output

Recall that lm_schnell works with quantitative traits only, and that because MCMC is performed at each position, the number of MC iterations needed is less. Since the number of MC iterations required is less, we must edit the parameter file `ped73_qu.par' to reflect this (just like we did when running the lm_lods example). Instructions are located near the end of the parameter file, and are given below:

 
	#For actual analyses, recommended number of iterations is
	#on the order of 10^5
set MC iterations 3000            #1
check progress MC iterations 1000      
set global MCMC

	#TO RUN LM_SCHNELL, comment out the line marked #1 (above),
	#and uncomment the line marked #2 (below). This effectively 
	#reduces the number of MC iterations

	#Recall that lm_lods and lm_shnell require less iterations 
	#(order of 10^4) than other programs 

#set MC iterations 300            #2

Under the subdirectory `Lodscores/', run the example with the following command:

 
./lm_schnell ped73_qu.par

Since additive variance is not specified in the parameter file, the default value 0 is used. This example takes a while to finish.

 
 ESTIMATED LOD SCORES

  Component 1

    The largest eigenvalue:          2.38058

    The second largest eigenvalue:   1.84655

    Cumulative from left  :          3.47316

    Cumulative from right :          0.28792

    LOD scores:
    position     female       male      eigen       left      right
           0 -115.12925 -115.12925    0.04135    0.01177   -0.52896
           1  -80.47190  -80.47190   -0.04939    0.04327   -0.49746
           2  -45.81454  -45.81454   -0.20917    0.10753   -0.43320
           3  -17.83375  -17.83375   -0.72080    0.20552   -0.33520
           4   -5.26803   -5.26803   -1.42463   -0.11293   -0.65366
           5    3.00000    3.00000   -1.90715   -0.16779   -0.70852
           6    7.00000    7.00000   -2.20055   -0.23907   -0.77979
           7   13.00000   13.00000   -2.78293   -0.06788   -0.60860
           8   17.00000   17.00000   -3.33181   -0.14982   -0.69055
           9   23.00000   23.00000   -4.36919    0.01748   -0.52324
          10   27.00000   27.00000   -4.61200    0.09763   -0.44309
          11   33.00000   33.00000   -4.76603    0.93494    0.39421
          12   37.00000   37.00000   -4.92469    1.19967    0.65894
          13   43.00000   43.00000   -5.47771    1.22628    0.68555
          14   47.00000   47.00000   -5.74826    1.36085    0.82013
          15   53.00000   53.00000   -6.35674    0.74257    0.20184
          16   57.00000   57.00000   -6.15321    0.48212   -0.05860
          17   63.00000   63.00000   -6.19531   -0.03028   -0.57100
          18   67.00000   67.00000   -6.27084   -0.56559   -1.10631
          19   73.00000   73.00000   -4.94832   -0.61375   -1.15447
          20   77.00000   77.00000   -4.35057   -0.29956   -0.84028
          21   83.00000   83.00000   -3.34770    0.11962   -0.42110
          22   87.00000   87.00000   -2.86960    0.22810   -0.31263
          23   95.26803   95.26803   -1.58121    0.97457    0.43385
          24  107.83375  107.83375   -0.68635    1.08899    0.54826
          25  135.81454  135.81454   -0.36267    0.83854    0.29781
          26  170.47190  170.47190   -0.24994    0.67770    0.13698
          27  205.12925  205.12925   -0.08595    0.61535    0.07462

The `eigen', `left' and `right' columns have the same interpretation as in lm_lods.

For more information regarding the MCMC parameters and diagnostic output, See MCMC parameters and options.


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This document was generated by Elizabeth Thompson on September, 10 2010 using texi2html