Department of Neurological Surgery and the Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA 94143, USA.
Bioinformatics. 2018 Sep 15;34(18):3217-3219. doi: 10.1093/bioinformatics/bty316.
Single-cell RNA-sequencing (scRNA-seq) has enabled studies of tissue composition at unprecedented resolution. However, the application of scRNA-seq to clinical cancer samples has been limited, partly due to a lack of scRNA-seq algorithms that integrate genomic mutation data.
To address this, we present.
COpy-Number analysis In single-Cell RNA-Sequencing. CONICS is a software tool for mapping gene expression from scRNA-seq to tumor clones and phylogenies, with routines enabling: the quantitation of copy-number alterations in scRNA-seq, robust separation of neoplastic cells from tumor-infiltrating stroma, inter-clone differential-expression analysis and intra-clone co-expression analysis.
CONICS is written in Python and R, and is available from https://github.com/diazlab/CONICS.
Supplementary data are available at Bioinformatics online.
单细胞 RNA 测序（scRNA-seq）使人们能够以前所未有的分辨率研究组织组成。然而，scRNA-seq 在临床癌症样本中的应用受到限制，部分原因是缺乏整合基因组突变数据的 scRNA-seq 算法。
为了解决这个问题，我们提出了。
单细胞 RNA 测序中的拷贝数分析。CONICS 是一种将 scRNA-seq 中的基因表达映射到肿瘤克隆和系统发育的软件工具，其例程可实现：scRNA-seq 中拷贝数改变的定量、肿瘤浸润基质中肿瘤细胞的稳健分离、克隆间差异表达分析和克隆内共表达分析。
CONICS 是用 Python 和 R 编写的，可以从 https://github.com/diazlab/CONICS 获得。
补充数据可在生物信息学在线获得。
