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github上面的单细胞转录组数据处理工具列表大全

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发表于 2017-9-14 10:20:11 | 显示全部楼层 |阅读模式
已经有一系列的软件和数据库资源来加快单细胞转录组测序的数据处理了,比如在GitHub上面的[Awesome Single Cell](http://go.nature.com/2rmb1hp)里面就列出来了超过70多款软件和工具,涵盖着单细胞转录组测序的数据处理方方面面。华盛顿大学的生物学家Cole Trapnell(Cole Trapnell, a biologist at the University of Washington in Seattle.)说道:聚焦于单细胞转录组测序却常常是上千个样本。那些设计来处理少量样本数据的工具通常对于这些大批量样本数据表现很差,或者消耗成千上万倍的时间的数据处理的软件已经很可观了,自成体系
Software packagesRNA-seq
  • anchor - [Python] - ⚓ Find bimodal, unimodal, and multimodal features in your data
  • BackSPIN - [Python] - Biclustering algorithm developed taking into account intrinsic features of single-cell RNA-seq experiments.
  • BASiCS - [R] - Bayesian Analysis of single-cell RNA-seq data. Estimates cell-specific normalization constants. Technical variability is quantified based on spike-in genes. The total variability of the expression counts is decomposed into technical and biological components. BASiCS can also identify genes with differential expression/over-dispersion between two or more groups of cells.
  • BEARscc - [R] - BEARscc makes use of ERCC spike-in measurements to model technical variance as a function of gene expression and technical dropout effects on lowly expressed genes.
  • bonvoyage - [Python] -
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