Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.
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DOI:
10.1186/s13059-014-0550-8
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发表时间:
2014
期刊:
影响因子:
12.3
通讯作者:
Anders S
Anders S
中科院分区:
生物学1区
文献类型:
--
作者:
Love MI;Huber W;Anders S

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在比较的高通量测序分析中,一项基本任务是分析计数数据,如RNA-SEQ中的每个基因的读取计数,以寻找实验条件下系统变化的证据。小重复数、离散性、大动态范围和离群值的存在需要合适的统计方法。我们提出了一种计数数据的差分分析方法DESeq2,它使用对离散度和褶皱变化的收缩估计来提高估计的稳定性和可解释性。这使得更多的定量分析集中在强度上,而不仅仅是差异表达的存在。DESEQ2程序包可在http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html.上获得本文的在线版本(doi:10.1186/s13059-0140550-8)包含补充材料,授权用户可以使用。
In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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发表时间: 2012-04
期刊: Biostatistics (Oxford, England)
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