scispace - formally typeset
Open AccessJournal ArticleDOI

voom: precision weights unlock linear model analysis tools for RNA-seq read counts

TLDR
New normal linear modeling strategies are presented for analyzing read counts from RNA-seq experiments, and the voom method estimates the mean-variance relationship of the log-counts, generates a precision weight for each observation and enters these into the limma empirical Bayes analysis pipeline.
Abstract
New normal linear modeling strategies are presented for analyzing read counts from RNA-seq experiments. The voom method estimates the mean-variance relationship of the log-counts, generates a precision weight for each observation and enters these into the limma empirical Bayes analysis pipeline. This opens access for RNA-seq analysts to a large body of methodology developed for microarrays. Simulation studies show that voom performs as well or better than count-based RNA-seq methods even when the data are generated according to the assumptions of the earlier methods. Two case studies illustrate the use of linear modeling and gene set testing methods.

read more

Content maybe subject to copyright    Report

Citations
More filters
Journal ArticleDOI

Dysregulation of brain and choroid plexus cell types in severe COVID-19.

TL;DR: In this article, single-nucleus transcriptomes of frontal cortex and choroid plexus samples from patients with COVID-19 reveal pathological cell states that are similar to those associated with human neurodegenerative diseases and chronic brain disorders.
Journal ArticleDOI

Sex Differences in Nucleus Accumbens Transcriptome Profiles Associated with Susceptibility versus Resilience to Subchronic Variable Stress

TL;DR: It is reported that exposure to subchronic variable stress (SCVS) induces depression-associated behaviors in female mice, whereas males are resilient as they do not develop these behavioral abnormalities, and transcriptional analysis of nucleus accumbens revealed markedly different patterns of stress regulation of gene expression between the sexes.
Journal ArticleDOI

RNA-Seq workflow: gene-level exploratory analysis and differential expression

TL;DR: This work walks through an end-to-end gene-level RNA-Seq differential expression workflow using Bioconductor packages to perform exploratory data analysis (EDA) for quality assessment and to explore the relationship between samples.
Journal ArticleDOI

AP-1 Transcription Factors and the BAF Complex Mediate Signal-Dependent Enhancer Selection

TL;DR: It is demonstrated how environmental signals acting via FOS/JUN and BAF coordinate with cell-type-specific TFs to select enhancer repertoires that enable differentiation during development.
References
More filters
Journal ArticleDOI

edgeR: a Bioconductor package for differential expression analysis of digital gene expression data.

TL;DR: EdgeR as mentioned in this paper is a Bioconductor software package for examining differential expression of replicated count data, which uses an overdispersed Poisson model to account for both biological and technical variability and empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference.
Book

Generalized Linear Models

TL;DR: In this paper, a generalization of the analysis of variance is given for these models using log- likelihoods, illustrated by examples relating to four distributions; the Normal, Binomial (probit analysis, etc.), Poisson (contingency tables), and gamma (variance components).
Journal ArticleDOI

featureCounts: an efficient general-purpose program for assigning sequence reads to genomic features

TL;DR: FeatureCounts as discussed by the authors is a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments, which implements highly efficient chromosome hashing and feature blocking techniques.
Journal ArticleDOI

Differential expression analysis for sequence count data.

Simon Anders, +1 more
- 27 Oct 2010 - 
TL;DR: A method based on the negative binomial distribution, with variance and mean linked by local regression, is proposed and an implementation, DESeq, as an R/Bioconductor package is presented.
Related Papers (5)