RNA-Seq data processing and gene expression analysis

Edit me

Introduction

This document outlines the essential steps in the process of analyzing gene expression data using RNA sequencing (mRNA, specifically), and recommends commonly used tools and techniques for this purpose. It is assumed in this document that the experimental design is simple and that differential expression is being assessed between 2 experimental conditions, i.e. a simple 1:1 comparison, with some information about analyzing data from complex experimental designs. The focus of the SOP is on single-end strand-specific reads, however special measures to be taken for analysis of paired-end data are also briefly discussed. The recommended coverage for RNA-Seq on human samples is 30-50 million reads (single-end), with a minimum of three replicates per condition, preferably more if one can budget accordingly. Preference is also generally given for a higher number of replicates with a lower per-sample sequence yield (15-20 million reads) if there is a tradeoff between the number of reads per sample and the total number of replicates.

The procedures outlined below are recommendations to the H3ABioNet groups planning to do differential gene expression analysis on human RNA-Seq data, and are not meant to be prescriptive. Our goal is to help the groups set up their procedures and workflows, and to provide an overview of the main steps involved and the tools that can be used to implement them.

Bibliography