In easyRNASeq: Count summarization and normalization for RNA-Seq data

Introduction

This vignette provides the implementation of the procedure described in point 7 of our Guidelines for RNA-Seq data analysis[^1] protocol available from the Epigenesys website.

Briefly, it details the step necessary to: 1. create a non-redundant annotation

1. count reads per feature

2. pre-analyse the data, i.e. assess the pertinence of the samples' charateristics in the light of their biological provenance; i.e. in other words perform a so called "biological QA" using assessment methods such as Principal Component Analysis, Multi-dimensional Scaling, Hierarcical Clustering, etc.

The aim of this vignette is to go through these steps using the easyRNASeq package, hence the rationale of the implementation will not be discussed, albeit relevant litterature will be pointed at when necessarry.

Throughout this vignette we are going to replicate the analysis conducted in Robinson, Delhomme et al.[@Robinson:2014p6362], a study looking at sexual dimorphism in Eurasian aspen.

To perform the listed steps, we need to instantiate a number of objects to store the minimal set of parameters describing the conducted RNA-Seq experiment, e.g. the BAM files location, the annotation location and type, the sequencing parameters, etc.

To get started with this process, we load the package into our R session:

library(easyRNASeq)

before instantiating an AnnotParam object informing on the location and type of the annotation to be used.

vDir <- vignetteData()

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easyRNASeq documentation built on April 30, 2020, 2 a.m.