CONICS integrates scRNA-seq with DNA sequencing to map gene expression to tumor sub-clones
CONICS integrates scRNA-seq with DNA sequencing to map gene expression to tumor sub-clones
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DOI：
10.1093/bioinformatics/bty316
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发表时间：
2018-09-15
期刊：
影响因子：
5.8
通讯作者：
Diaz, Aaron
中科院分区：
文献类型：
--
作者：
Muller, Soren;Cho, Ara;Diaz, Aaron
动机：单细胞RNA测序（scRNA-seq）使组织组成的研究在前所未有的分辨率。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data.Results的scRNA-seq算法：为了解决这个问题，我们提出了CONICS：单细胞RNA测序中的拷贝数分析。CONICS是一种软件工具，用于将基因表达从scRNA-seq映射到肿瘤克隆和肿瘤基因，其例程能够：定量scRNA-seq中的拷贝数改变，从肿瘤浸润基质中稳健分离肿瘤细胞，克隆间差异表达分析和克隆内共表达分析。可用性和实施：CONICS用Python和R编写，可从https://github.com/diazlab/CONICS.Contact：aaron.迪亚兹@.ucsf. edu获得补充信息：补充数据可在Bioinformatics在线获得。
Motivation: 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.Results: To address this, we present CONICS: 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.Availability and implementation: CONICS is written in Python and R, and is available from https://github.com/diazlab/CONICS.Contact: aaron.diaz@.ucsf.eduSupplementary information: Supplementary data are available at Bioinformatics online.