9.5 Running lm_pval example and sample output

Under the subdirectory `Nonparametric/', run the lm_pval example by typing:

lm_pval ped73_pval.par > pval.out

A portion of the output giving fuzzy p-values is below. See `pval.out' for the entire output file.

Combined distribution of fuzzy p-values, by locus: pval maxim marker-1 marker-2 marker-3 marker-4 marker-5 marker-6 marker-7 marker-8 marker-9 marker-10 0.00 0.000 0.000 0.000 0.000 0.000 0.000 0.001 0.001 0.000 0.000 0.000 0.01 0.004 0.000 0.000 0.000 0.004 0.000 0.009 0.011 0.000 0.000 0.000 0.02 0.008 0.000 0.000 0.000 0.009 0.005 0.020 0.024 0.005 0.005 0.005 0.03 0.011 0.000 0.000 0.000 0.016 0.019 0.033 0.036 0.019 0.019 0.019 0.04 0.015 0.000 0.000 0.000 0.023 0.032 0.045 0.049 0.032 0.032 0.032 0.05 0.019 0.000 0.000 0.000 0.029 0.046 0.058 0.062 0.046 0.046 0.046

Interpretation of the output is as follows. For a certain p value, say, `0.05', the columns labelled `marker-1' through `marker-10' give the probability of obtaining a p-value less than this p value 0.05 over the sampling run at each marker, i.e., the power. The column labelled `maxim' gives the maximum over all loci. Because the trait used in simulating the marker data for this example does not have a strong signal, each marker has very little power (ranging from 0.000 to 0.062) and the multilocus power is only 1.9%.