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edgeR
Bioconductor version: Release (3.19) Differential expression analysis of RNA-seq expression profiles with biological replication. Implements a range of statistical methodology based on the negative binomial distributions, including empirical Bayes estimation, exact tests, generalized linear models and quasi-likelihood tests. As well as RNA-seq, it be applied to differential signal analysis of othe
Bowtie 2: Manual
Langmead B, Salzberg S. Fast gapped-read alignment with Bowtie 2. Nature Methods. 2012, 9:357-359. Langmead B, Wilks C, Antonescu V, Charles R. Scaling read aligners to hundreds of threads on general-purpose processors. Bioinformatics Vol 35, Iss 3, 2019, pp 421–432. Introduction Bowtie 2 is an ultrafast and memory-efficient tool for aligning sequencing reads to long reference sequences. It is par
QoRTs: a comprehensive toolset for quality control and data processing of RNA-Seq experiments - BMC Bioinformatics
Software Open access Published: 19 July 2015 QoRTs: a comprehensive toolset for quality control and data processing of RNA-Seq experiments Stephen W. Hartley1 & James C. Mullikin1 BMC Bioinformatics volume 16, Article number: 224 (2015) Cite this article BackgroundHigh-throughput next-generation RNA sequencing has matured into a viable and powerful method for detecting variations in transcript exp
How to use DESeq to analyse RNAseq data | Dave the Data Dero
Several packages have been written to measure gene expression differences using RNAseq data. In this post I’m going to do a run through of the popular R based DESeq package. Basically, I’m just following along with the packages Vignette which is really well written and informative! For the test data I’m using 2 treatments, with 3 biological reps each containing 750K reads (yes its small). A. Count
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GitHub - alexdobin/STAR: RNA-seq aligner
GitHub - jdblischak/singleCellSeq: Batch effects and the effective design of single-cell gene expression studies
Single-cell RNA-seq discovers a wealth of new RNA markers that define discrete groups of neurons | RNA-Seq Blog
GitHub - PMBio/scLVM: scLVM is a modelling framework for single-cell RNA-seq data that can be used to dissect the observed heterogeneity into different sources, thereby allowing for the correction of confounding sources of variation.
A novel approach for resolving differences in single-cell gene expression patterns from zygote to blastocyst - PubMed
A comparative study of techniques for differential expression analysis on RNA-Seq data | RNA-Seq Blog
http://www.bioconductor.org/packages/release/bioc/vignettes/sRAP/inst/doc/sRAP.pdf
gage
Smile. Tomorrow will be worse. - AABBDD
rpkmforgenes.py manual
Cufflinks
TopHat
The hidden treasure in RNA-seq
Gitools - A framework for analysis and visualization of genomic data
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