Gene set analysis controlling for length bias in RNA-seq experiments

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• 作者：Xing Ren ; Qiang Hu ; Song Liu ; Jianmin Wang ; Jeffrey C. Miecznikowski
• 关键词：RNA ; seq ; Gene set analysis ; Gene length bias ; Maxmean statistic ; Restandardization
• 刊名：BioData Mining
• 出版年：2017
• 出版时间：December 2017
• 年：2017
• 卷：10
• 期：1
• 全文大小：1174KB
• 刊物主题：Computer Appl. in Life Sciences; Computational Biology/Bioinformatics; Data Mining and Knowledge Discovery; Bioinformatics; Algorithms;
• 出版者：BioMed Central
• ISSN：1756-0381
• 卷排序：10

文摘

BackgroundIn gene set analysis, the researchers are interested in determining the gene sets that are significantly correlated with an outcome, e.g. disease status or treatment. With the rapid development of high throughput sequencing technologies, Ribonucleic acid sequencing (RNA-seq) has become an important alternative to traditional expression arrays in gene expression studies. Challenges exist in adopting the existent algorithms to RNA-seq data given the intrinsic difference of the technologies and data. In RNA-seq experiments, the measure of gene expression is correlated with gene length. This inherent correlation may cause bias in gene set analysis.