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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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