Evaluation of methods for differential expression analysis on multi-group RNA-seq count data

compcodeR--an R package for benchmarking differential expression methods for RNA-seq data

(2014) C. Soneson   BIOINFORMATICS

Differential expression analysis of RNA-seq data at single-base resolution

(2014) A. C. Frazee et al.   BIOSTATISTICS

Fold change rank ordering statistics: a new method for detecting differentially expressed genes

(2014) Doulaye Dembélé et al.   BMC BIOINFORMATICS

IUTA: a tool for effectively detecting differential isoform usage from RNA-Seq data

(2014) Liang Niu et al.   BMC GENOMICS

Bootstrap-based differential gene expression analysis for RNA-Seq data with and without replicates

(2014) Sahar Al Seesi et al.   BMC GENOMICS

DegPack: A web package using a non-parametric and information theoretic algorithm to identify differentially expressed genes in multiclass RNA-seq samples

(2014) Jaehyun An et al.   METHODS

Robustly detecting differential expression in RNA sequencing data using observation weights

(2014) Xiaobei Zhou et al.   NUCLEIC ACIDS RESEARCH

A Comparative Study of Techniques for Differential Expression Analysis on RNA-Seq Data

(2014) Zong Hong Zhang et al.   PLoS One

Power analysis and sample size estimation for RNA-Seq differential expression

(2014) Travers Ching et al.   RNA

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

(2014) Charity W Law et al.   GENOME BIOLOGY

SplicingCompass: differential splicing detection using RNA-Seq data

(2013) Moritz Aschoff et al.   BIOINFORMATICS

EBSeq: an empirical Bayes hierarchical model for inference in RNA-seq experiments

(2013) Ning Leng et al.   BIOINFORMATICS

RNA-seq differential expression studies: more sequence or more replication?

(2013) Yuwen Liu et al.   BIOINFORMATICS

Empirical Bayesian analysis of paired high-throughput sequencing data with a beta-binomial distribution

(2013) Thomas J Hardcastle et al.   BMC BIOINFORMATICS

NPEBseq: nonparametric empirical bayesian-based procedure for differential expression analysis of RNA-seq data

(2013) Yingtao Bi et al.   BMC BIOINFORMATICS

A flexible count data model to fit the wide diversity of expression profiles arising from extensively replicated RNA-seq experiments

(2013) Mikel Esnaola et al.   BMC BIOINFORMATICS

TCC: an R package for comparing tag count data with robust normalization strategies

(2013) Jianqiang Sun et al.   BMC BIOINFORMATICS

A comparison of methods for differential expression analysis of RNA-seq data

(2013) Charlotte Soneson et al.   BMC BIOINFORMATICS

Comparison of software packages for detecting differential expression in RNA-seq studies

(2013) F. Seyednasrollah et al.   BRIEFINGS IN BIOINFORMATICS

Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data

(2013) Franck Rapaport et al.   GENOME BIOLOGY

Distributional fold change test – a statistical approach for detecting differential expression in microarray experiments

(2012) Vadim Farztdinov et al.   Algorithms for Molecular Biology

A normalization strategy for comparing tag count data

(2012) Koji Kadota et al.   Algorithms for Molecular Biology

A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis

(2012) M.-A. Dillies et al.   BRIEFINGS IN BIOINFORMATICS

Detecting differential usage of exons from RNA-seq data

(2012) S. Anders et al.   GENOME RESEARCH

Differential analysis of gene regulation at transcript resolution with RNA-seq

(2012) Cole Trapnell et al.   NATURE BIOTECHNOLOGY

Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation

(2012) Davis J. McCarthy et al.   NUCLEIC ACIDS RESEARCH

Evaluation of normalization methods in mammalian microRNA-Seq data

(2012) L. X. Garmire et al.   RNA

A powerful and flexible approach to the analysis of RNA sequence count data

(2011) Yi-Hui Zhou et al.   BIOINFORMATICS

Normalization, testing, and false discovery rate estimation for RNA-sequencing data

(2011) J. Li et al.   BIOSTATISTICS

Evaluating methods for ranking differentially expressed genes applied to microArray quality control data

(2011) Koji Kadota et al.   BMC BIOINFORMATICS

Finding consistent patterns: A nonparametric approach for identifying differential expression in RNA-Seq data

(2011) Jun Li et al.   STATISTICAL METHODS IN MEDICAL RESEARCH

From RNA-seq reads to differential expression results

(2011) Alicia Oshlack et al.   GENOME BIOLOGY

Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments

(2010) James H Bullard et al.   BMC BIOINFORMATICS

baySeq: Empirical Bayesian methods for identifying differential expression in sequence count data

(2010) Thomas J Hardcastle et al.   BMC BIOINFORMATICS

A scaling normalization method for differential expression analysis of RNA-seq data

(2010) Mark D Robinson et al.   GENOME BIOLOGY

Differential expression analysis for sequence count data

(2010) Simon Anders et al.   GENOME BIOLOGY

Ranking differentially expressed genes from Affymetrix gene expression data: methods with reproducibility, sensitivity, and specificity

(2009) Koji Kadota et al.   Algorithms for Molecular Biology

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

(2009) M. D. Robinson et al.   BIOINFORMATICS

Sex-specific and lineage-specific alternative splicing in primates

(2009) R. Blekhman et al.   GENOME RESEARCH

A weighted average difference method for detecting differentially expressed genes from microarray data

(2008) Koji Kadota et al.   Algorithms for Molecular Biology

RNA-seq: An assessment of technical reproducibility and comparison with gene expression arrays

(2008) J. C. Marioni et al.   GENOME RESEARCH

Mapping and quantifying mammalian transcriptomes by RNA-Seq

(2008) Ali Mortazavi et al.   NATURE METHODS

RNA-Seq: a revolutionary tool for transcriptomics

(2008) Zhong Wang et al.   NATURE REVIEWS GENETICS

A Global View of Gene Activity and Alternative Splicing by Deep Sequencing of the Human Transcriptome

(2008) M. Sultan et al.   SCIENCE