A rank-based statistical test for measuring synergistic effects between two gene sets

作者：Shiraishi Yuichi^*; Okada Hatakeyama Mariko; Miyano Satoru

来源：Bioinformatics, 2011, 27(17): 2399-2405.

DOI：10.1093/bioinformatics/btr382

Motivation: Due to recent advances in high-throughput technologies, data on various types of genomic annotation have accumulated. These data will be crucially helpful for elucidating the combinatorial logic of transcription. Although several approaches have been proposed for inferring cooperativity among multiple factors, most approaches are haunted by the issues of normalization and threshold values.
Results: In this article, we propose a rank-based non-parametric statistical test for measuring the effects between two gene sets. This method is free from the issues of normalization and threshold value determination for gene expression values. Furthermore, we have proposed an efficient Markov chain Monte Carlo method for calculating an approximate significance value of synergy. We have applied this approach for detecting synergistic combinations of transcription factor binding motifs and histone modifications.

• 出版日期2011-9-1
• 单位河北医科大学