Computational and analytical challenges in single-cell transcriptomics

O Stegle, SA Teichmann, JC Marioni - Nature Reviews Genetics, 2015 - nature.com
Nature Reviews Genetics, 2015nature.com
The development of high-throughput RNA sequencing (RNA-seq) at the single-cell level has
already led to profound new discoveries in biology, ranging from the identification of novel
cell types to the study of global patterns of stochastic gene expression. Alongside the
technological breakthroughs that have facilitated the large-scale generation of single-cell
transcriptomic data, it is important to consider the specific computational and analytical
challenges that still have to be overcome. Although some tools for analysing RNA-seq data …
Abstract
The development of high-throughput RNA sequencing (RNA-seq) at the single-cell level has already led to profound new discoveries in biology, ranging from the identification of novel cell types to the study of global patterns of stochastic gene expression. Alongside the technological breakthroughs that have facilitated the large-scale generation of single-cell transcriptomic data, it is important to consider the specific computational and analytical challenges that still have to be overcome. Although some tools for analysing RNA-seq data from bulk cell populations can be readily applied to single-cell RNA-seq data, many new computational strategies are required to fully exploit this data type and to enable a comprehensive yet detailed study of gene expression at the single-cell level.
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