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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.

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Role of duplicate genes in determining the tissue-selectivity of hereditary diseases.

TL;DR: It is shown for the first time at large-scale via quantitative analysis of omics datasets that, preferentially in the disease-manifesting tissues, paralogs are under-expressed relative to causal genes in more than half of the diseases.
Journal ArticleDOI

Determining breast cancer histological grade from RNA-sequencing data

TL;DR: Gene- and isoform-level expression data from RNA-sequencing could be utilised to differentiate HG1 and HG3 breast cancer tumours with high accuracy and a large number of novel genes and isoforms associated with HG were identified.
Journal ArticleDOI

Sex-Specific Control of Human Heart Maturation by the Progesterone Receptor

TL;DR: In this article, the progesterone receptor was identified as a key mediator of sexdependent transcriptional programs during cardiomyocyte maturation, and functional validation studies of sex steroids implicated in cardiac maturation were performed in human pluripotent stem cell-derived cardiac organoids and mice.
References
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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.
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