Differential expression analysis of RNA sequencing data by incorporating non-exonic mapped reads

Robustly detecting differential expression in RNA sequencing data using observation weights

(2014) Xiaobei Zhou et al.   NUCLEIC ACIDS RESEARCH

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

(2014) Charity W Law et al.   GENOME BIOLOGY

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

(2013) Ning Leng et al.   BIOINFORMATICS

Efficient experimental design and analysis strategies for the detection of differential expression using RNA-Sequencing

(2012) José A Robles et al.   BMC GENOMICS

Landscape of transcription in human cells

(2012) Sarah Djebali et al.   NATURE

Total RNA sequencing reveals nascent transcription and widespread co-transcriptional splicing in the human brain

(2011) Adam Ameur et al.   NATURE STRUCTURAL & MOLECULAR BIOLOGY

Detection and Removal of Biases in the Analysis of Next-Generation Sequencing Reads

(2011) Schraga Schwartz et al.   PLoS One

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

(2010) Thomas J Hardcastle et al.   BMC BIOINFORMATICS

Transcribed dark matter: meaning or myth?

(2010) C. P. Ponting et al.   HUMAN MOLECULAR GENETICS

Most “Dark Matter” Transcripts Are Associated With Known Genes

(2010) Harm van Bakel et al.   PLOS BIOLOGY

Differential expression analysis for sequence count data

(2010) Simon Anders et al.   GENOME BIOLOGY

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

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

Mapping and quantifying mammalian transcriptomes by RNA-Seq

(2008) Ali Mortazavi et al.   NATURE METHODS