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Title:
Itโs DE-licious: A Recipe for Differential Expression Analyses of RNA-seq Experiments Using Quasi-Likelihood Methods in edgeR | SpringerLink
Description:
RNA sequencing (RNA-seq) is widely used to profile transcriptional activity in biological systems. Here we present an analysis pipeline for differential expression analysis of RNA-seq experiments using the Rsubread and edgeR software packages. The basic pipeline...
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pubmed, google, scholar, article, analysis, data, expression, smyth, rnaseq, differential, methods, cas, central, research, protocol, bioinformatics, experiments, nat, privacy, cookies, content, information, publish, edger, lun, sequencing, gene, chapter, search, statistical, quasilikelihood, chen, read, access, robinson, biol, download, springer, usd, personal, log, journal, genomics, analyses, aaron, gordon, book, biology, rna, biological,
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high-throughput sequencing data month download article/chapter multifactor rna-seq experiments org/smyth/pubs/robustebayespreprint rna sequencing data privacy choices/manage cookies mccarthy dj differential expression analysis moderated statistical tests eliza hall institute medical research council rna-sequence data gene expression estimation device instant download rna-seq data differential expression analyses author information authors rna-seq experiments including complex comparisons gene set testing detecting differential expression european economic area profile transcriptional activity mammary gland cells quantifying mammalian transcriptomes scalable read mapping shrunken dispersion estimates small-sample estimation negative binomial dispersion egf-mediated induction alveolar cell survival discovering splice junctions vernon puzey scholarship assessing differential expression journal finder publish conditions privacy policy quasi-likelihood features complex microarray experiments statistical genomics accepting optional cookies quasi-likelihood methods scaling normalization method main content log edger software packages check access empirical bayes methods ethics access dna sequencing yunshun chenย &ย gordon national institutes
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ScholarlyArticle:
headline:Itโs DE-licious: A Recipe for Differential Expression Analyses of RNA-seq Experiments Using Quasi-Likelihood Methods in edgeR
pageEnd:416
pageStart:391
image:https://media.springernature.com/w153/springer-static/cover/book/978-1-4939-3578-9.jpg
genre:
Springer Protocols
isPartOf:
name:Statistical Genomics
isbn:
978-1-4939-3578-9
978-1-4939-3576-5
type:Book
publisher:
name:Springer New York
logo:
url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
type:ImageObject
type:Organization
author:
name:Aaron T. L. Lun
affiliation:
name:Walter and Eliza Hall Institute of Medical Research
address:
name:Walter and Eliza Hall Institute of Medical Research, Parkville, Australia
type:PostalAddress
type:Organization
type:Person
name:Yunshun Chen
affiliation:
name:Walter and Eliza Hall Institute of Medical Research
address:
name:Walter and Eliza Hall Institute of Medical Research, Parkville, Australia
type:PostalAddress
type:Organization
type:Person
name:Gordon K. Smyth
affiliation:
name:Walter and Eliza Hall Institute of Medical Research
address:
name:Walter and Eliza Hall Institute of Medical Research, Parkville, Australia
type:PostalAddress
type:Organization
type:Person
keywords:RNA-seq, Differential expression, Generalized linear models, Quasi-likelihood, Variability, Read alignment, Read counts
description:RNA sequencing (RNA-seq) is widely used to profile transcriptional activity in biological systems. Here we present an analysis pipeline for differential expression analysis of RNA-seq experiments using the Rsubread and edgeR software packages. The basic pipeline includes read alignment and counting, filtering and normalization, modelling of biological variability and hypothesis testing. For hypothesis testing, we describe particularly the quasi-likelihood features of edgeR. Some more advanced downstream analysis steps are also covered, including complex comparisons, gene ontology enrichment analyses and gene set testing. The code required to run each step is described, along with an outline of the underlying theory. The chapter includes a case study in which the pipeline is used to study the expression profiles of mammary gland cells in virgin, pregnant and lactating mice.
datePublished:2016
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Book:
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isbn:
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978-1-4939-3576-5
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name:Springer New York
logo:
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name:Walter and Eliza Hall Institute of Medical Research
address:
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affiliation:
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address:
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name:Walter and Eliza Hall Institute of Medical Research, Parkville, Australia
name:Walter and Eliza Hall Institute of Medical Research, Parkville, Australia
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