Open AccessDEgenes Hunter - A Flexible R Pipeline for Automated RNA-seq Studies in Organisms without Reference Genome
Author(s) -
Isabel González Gayte,
Rocío Bautista Moreno,
Pedro Seoane-Zonjic,
M. Gonzalo Claros
Publication year - 2017
Publication title -
genomics and computational biology
Language(s) - English
Resource type - Journals
ISSN - 2365-7154
DOI - 10.18547/gcb.2017.vol3.iss3.e31
Subject(s) - computer science , pipeline (software) , ranking (information retrieval) , set (abstract data type) , scripting language , interpretation (philosophy) , genome , computational biology , data mining , rna seq , artificial intelligence , biology , gene , transcriptome , gene expression , genetics , programming language
Differential gene expression based on RNA-seq is widely used. Bioinformatics skills are required since no algorithm is appropriate for all experimental designs. Moreover, when working with organisms without reference genome, functional analysis is less than straightforward in most situations. DEgenes Hunter, an attempt to automate the process, is based on two independent scripts, one for differential expression and one for functional interpretation. Based on replicates, the R script decides which of the edgeR, DEseq2, NOISeq and limma algorithms are appropriate. It performs quality control calculations and provides the prevalent, most reliable, set of differentially expressed genes, and lists all other possible candidates for further functional interpretation. It also provides a combined P-value that allows differentially expressed genes ranking. It has been tested with synthetic and real-world datasets, showing in both cases ease of use and reliable results. With real data, DEgenes Hunter offers straightforward functional interpretation.