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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Computational and analytical challenges in single-cell transcriptomics
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RNA-Seq gene expression estimation with read mapping uncertainty
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Human housekeeping genes, revisited.
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TL;DR: The major conceptual and practical challenges of high-throughput RNA sequencing, the general classes of solutions for each category, and the interdependence between these categories are highlighted and discussed.
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Count-based differential expression analysis of RNA sequencing data using R and Bioconductor
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TL;DR: This protocol presents a state-of-the-art computational and statistical RNA-seq differential expression analysis workflow largely based on the free open-source R language and Bioconductor software and, in particular, on two widely used tools, DESeq and edgeR.
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