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.