Tag Archives: edgeR

Differential expression (DE) analysis of RNA-seq data still poses inferential challenges, such as handling of transcripts characterized by low expression levels. In this study, researchers from Kansas State University used a plasmode-based approach to assess the relative performance of alternative ...

A team led by researchers at the National Heart Lung and Blood Institute sequenced over 700 individuals from the Drosophila Genetic Reference Panel with the goal of identifying the optimal analysis approach for the detection of differential gene expression among ...

Sequencing is widely used to discover associations between microRNAs (miRNAs) and diseases. However, the negative binomial distribution (NB) and high dimensionality of data obtained using sequencing can lead to low-power results and low reproducibility. Several statistical learning algorithms have been ...

from RPubs by Alex Chitsazan Overview This is a script that will do differential gene expression (DGE) analysis for RNA-seq experiments using the bioconductor package edgeR. Project Details To give background on this project, this is a RNA-seq project that ...

A number of algorithms exist for analysing RNA-sequencing data to infer profiles of differential gene expression. Problems inherent in building algorithms around statistical models of over dispersed count data are formidable and frequently lead to non-uniform p-value distributions for null-hypothesis ...

It is crucial for researchers to optimize RNA-seq experimental designs for differential expression detection. Currently, the field lacks general methods to estimate power and sample size for RNA-Seq in complex experimental designs, under the assumption of the negative binomial distribution. ...

Pooled short hairpin RNA sequencing (shRNA-seq) screens are becoming increasingly popular in functional genomics research, and there is a need to establish optimal analysis tools to handle such data. This open-source shRNA processing pipeline in edgeR provides a complete analysis ...

Recent advances in next-generation sequencing technology allow high-throughput cDNA sequencing (RNA-Seq) to be widely applied in transcriptomic studies, in particular for detecting differentially expressed genes between groups. Many software packages have been developed for the identification of differentially expressed genes ...