Multiple factor comparison of various scores for MCMC
linkage analysis:
Application of shell scripts
Jianzhong Ma
A set of simulated pedigree data were analyzed using the Bayesian Monte Carlo Markov
chain (MCMC) techniques (as implemented in the program Loki), in order to examine
and compare several summary scores for assessing the significance of linkage. These
scores include the marginal posterior probability, the L-score (i.e. the Bayes factor), and
the LOP score, which is defined as the log of the posterior placement probability ratio
between the true and pseudo chromosomes, and were calculated using both the hit-count
and the Rao-Blackwell methods. The factors affecting the scores are (1) the marker
distance, (2) the data-missing pattern, (3) the number of families, (4) the quantitative trait
size, and (5) the linkage status of the true chromosome. The results showed that these
scores are in general in agreement with each other. Technically, various Unix shell script
and utilities, such as bash, sed, awk, and gnuplot, were employed in each step of this
study, from the setup, data reformatting and preparing, to data analysis.