[NamDU]Effect of the absolute statistic on gene-sampling gene-set analysis methods.

Prof. Nam (Bioinformatics Lab) published a research paper in the top ranked biostatistics journal Statistical Methods in Medical Research (top 4% among the 115 Statistics and Probability journals) on March 2015. Microarray and sequencing data are still costly and only a few sample replicates are used to contrast the test and control samples in most laboratories. To identify the altered pathways or functions from such small-sample data, gene-sampling gene-set analysis methods have been used. The biggest problem with this approach is the highly inflated false-positive rate.

In this paper, it is shown that incorporating the absolute gene statistic in gene-sampling gene-set analysis substantially reduces the false-positive rate and improves the overall discriminatory ability. Its effect was analyzed by power, false-positive rate, ROC and variance inflation factor for a number of simulated and real datasets.

ⓒ The Author(s) 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.