Soft Truncation Thresholding for Gene Set Analysis of RNA-seq Data: Application to a Vaccine Study

Overview

Journal Sci Rep

Specialty Science

Date 2013 Oct 10

PMID 24104466

Citations 11

Authors

Brooke L Fridley

Gregory D Jenkins

Diane E Grill

Richard B Kennedy

Gregory A Poland

Ann L Oberg

Affiliations

Soon will be listed here.

Abstract

Gene set analysis (GSA) has been used for analysis of microarray data to aid the interpretation and to increase statistical power. With the advent of next-generation sequencing, the use of GSA is even more relevant, as studies are often conducted on a small number of samples. We propose the use of soft truncation thresholding and the Gamma Method (GM) to determine significant gene set (GS), where a generalized linear model is used to assess per-gene significance. The approach was compared to other methods using an extensive simulation study and RNA-seq data from smallpox vaccine study. The GM was found to outperform other proposed methods. Application of the GM to the smallpox vaccine study found the GSs to be moderately associated with response, including focal adhesion (p = 0.04) and extracellular matrix receptor interaction (p = 0.05). The application of GSA to RNA-seq data will provide new insights into the genomic basis of complex traits.

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