A new fast method for copy number calling, tissue purity estimating and subclone inferring in cancer genome

Our new methods final launched on Nature Protocols, where we developed a series of methods and related C++/R combined software package,  Sclust(around 1.5Gb,大文件谨慎载). In Sclust, you can do copy number calling, cancer tissue purity estimating and clone and subclone structure inferring from normal-tumor paired whole genome/exon sequencing data.

先总结一下,我们方法的有如下点:

1. 可以准确地做copy number calling, tumor purity estimating,subclonal inferring;

2. subclonal inferring的速度超级快。4000~6000 个SNVs 的 clonal inferring 过程在个人电脑上只需3到5秒。

3. sclust 给出了每个集群的倍数树变异,目前还有少数个软件提供这个功能。

欢迎使用软件,欢迎咨询,欢迎交流。

联系邮件:yp.cun@outlook.com。 下面clonal 推断一些背景。

继续阅读“A new fast method for copy number calling, tissue purity estimating and subclone inferring in cancer genome”