Reproducible RNA-seq analysis using recount2

By L. Collado-Torres, Abhinav Nellore, K. Kammers, Shannon E. Ellis, M. Taub, Kasper D. Hansen, Andrew E. Jaffe, Ben Langmead, Jeffrey T. Leek. Nature Biotechnology, 2017

368 citations recorded by the source corpus.

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Subfields: Cancer Research, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/2e102a0f4b0b9595157423d9761723bfcdc73aa7

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Citations in the corpus

Genomic and Molecular Landscape of DNA Damage Repair Deficiency across The Cancer Genome Atlas (2018, positive): “This synonymous mutation may act by altering a splice donor to produce alternatively spliced transcripts that compromise TP53 function (Collado-Torres et al., 2017).”
RNA Sequencing Data: Hitchhiker's Guide to Expression Analysis (2018, methodology): “Figure 2: Ridge plot showing the progression of read length, depth and sample size in Sequence Read Archive (SRA) projects from the recount package [14] .”
A pathology atlas of the human cancer transcriptome (2017, positive): “Thanks to large open-access knowledge-based efforts, such as The Cancer Genome Atlas (TCGA) (5), the Human Protein Atlas (HPA) (6), the GTEx consortium (7), and recount2 (8), it is now possible to explore the genome-wide expression of individual genes in different tissues and cancers (9).”
Massive mining of publicly available RNA-seq data from human and mouse (2017, background): “Recent efforts such as recount2 (16) and RNAseqDB (17) attempt to simplify the access to gene expression data collected via RNA-seq to create a more unified data resource from fragmented repositories.”