RNA-Seq: a revolutionary tool for transcriptomics
TLDR
The RNA-Seq approach to transcriptome profiling that uses deep-sequencing technologies provides a far more precise measurement of levels of transcripts and their isoforms than other methods.Abstract:
RNA-Seq is a recently developed approach to transcriptome profiling that uses deep-sequencing technologies. Studies using this method have already altered our view of the extent and complexity of eukaryotic transcriptomes. RNA-Seq also provides a far more precise measurement of levels of transcripts and their isoforms than other methods. This article describes the RNA-Seq approach, the challenges associated with its application, and the advances made so far in characterizing several eukaryote transcriptomes.read more
Citations
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Journal ArticleDOI
RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome
Bo Li,Colin N. Dewey +1 more
TL;DR: It is shown that accurate gene-level abundance estimates are best obtained with large numbers of short single-end reads, and estimates of the relative frequencies of isoforms within single genes may be improved through the use of paired- end reads, depending on the number of possible splice forms for each gene.
Journal ArticleDOI
Sequencing technologies-the next generation
TL;DR: A technical review of template preparation, sequencing and imaging, genome alignment and assembly approaches, and recent advances in current and near-term commercially available NGS instruments is presented.
Journal ArticleDOI
De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis
Brian J. Haas,Alexie Papanicolaou,Moran Yassour,Moran Yassour,Manfred Grabherr,Philip D. Blood,Joshua C. Bowden,M. B. Couger,David Eccles,Bo Li,Matthias Lieber,Matthew D. MacManes,Michael Ott,Joshua Orvis,Nathalie Pochet,Nathalie Pochet,Francesco Strozzi,Nathan T. Weeks,Rick Westerman,Thomas William,Colin N. Dewey,Robert Henschel,Richard D. LeDuc,Nir Friedman,Aviv Regev +24 more
TL;DR: This protocol provides a workflow for genome-independent transcriptome analysis leveraging the Trinity platform and presents Trinity-supported companion utilities for downstream applications, including RSEM for transcript abundance estimation, R/Bioconductor packages for identifying differentially expressed transcripts across samples and approaches to identify protein-coding genes.
Journal ArticleDOI
A scaling normalization method for differential expression analysis of RNA-seq data
TL;DR: A simple and effective method for performing normalization is outlined and dramatically improved results for inferring differential expression in simulated and publicly available data sets are shown.
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GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses.
TL;DR: GEPIA (Gene Expression Profiling Interactive Analysis) fills in the gap between cancer genomics big data and the delivery of integrated information to end users, thus helping unleash the value of the current data resources.
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