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powsimR：用于批量和单细胞 RNA-seq 实验的功效分析。

powsimR: power analysis for bulk and single cell RNA-seq experiments.

机构信息

Anthropology & Human Genomics, Department of Biology II, Ludwig-Maximilians University, 82152 Munich, Germany.

出版信息

Bioinformatics. 2017 Nov 1;33(21):3486-3488. doi: 10.1093/bioinformatics/btx435.

DOI:10.1093/bioinformatics/btx435

Abstract

SUMMARY: Power analysis is essential to optimize the design of RNA-seq experiments and to assess and compare the power to detect differentially expressed genes in RNA-seq data. PowsimR is a flexible tool to simulate and evaluate differential expression from bulk and especially single-cell RNA-seq data making it suitable for a priori and posterior power analyses. AVAILABILITY AND IMPLEMENTATION: The R package and associated tutorial are freely available at https://github.com/bvieth/powsimR. CONTACT: vieth@bio.lmu.de or hellmann@bio.lmu.de. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

摘要

摘要：为了优化 RNA-seq 实验的设计，并评估和比较在 RNA-seq 数据中检测差异表达基因的能力，进行功效分析至关重要。PowsimR 是一种灵活的工具，可用于模拟和评估批量和特别是单细胞 RNA-seq 数据中的差异表达，使其适合先验和后验功效分析。

可用性和实现：R 包和相关教程可在 https://github.com/bvieth/powsimR 上免费获得。

联系方式：vieth@bio.lmu.de 或 hellmann@bio.lmu.de。

补充信息：补充数据可在生物信息学在线获得。

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