CHARTS: a web application for characterizing and comparing tumor subpopulations in publicly available single-cell RNA-seq data sets.
CHARTS: a web application for characterizing and comparing tumor subpopulations in publicly available single-cell RNA-seq data sets.
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DOI：
10.1186/s12859-021-04021-x
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发表时间：
2021-02-23
影响因子：
3
通讯作者：
Stewart R
中科院分区：
文献类型：
--
作者：
Bernstein MN;Ni Z;Collins M;Burkard ME;Kendziorski C;Stewart R
单细胞RNA-seq(scRNA-seq)能够在单细胞水平上分析全基因组的基因表达，这样做有助于洞察和了解组织内细胞的异质性。这在癌症中尤其重要，肿瘤和肿瘤微环境的异质性直接影响疾病的发展、维持和进展。虽然公开的scRNA-seq癌症数据集为更好地了解肿瘤进展、转移、耐药和免疫逃避的机制提供了前所未有的机会，但许多可用的信息一直没有得到充分利用，部分原因是缺乏可用于汇总和分析这些数据的工具。我们提出了表征肿瘤亚群(图表)，这是一个网络应用程序，用于在NCBI的基因表达总集中探索公开可用的scRNA-seq癌症数据集。更具体地说，图表可以探索单个基因的表达、细胞类型、恶性肿瘤状态、差异表达的基因，以及跨肿瘤和数据集的细胞亚群的基因集浓缩结果。除了Web应用程序，我们还提供了后端计算管道，该管道用于生成可在Web应用程序中探索的分析。Chart是一个易于使用的综合平台，用于在不断增长的公共scRNA-seq癌症数据集集合中探索肿瘤内的单细胞亚群。图表可以在charts.morgridge.org上免费获取。
Single-cell RNA-seq (scRNA-seq) enables the profiling of genome-wide gene expression at the single-cell level and in so doing facilitates insight into and information about cellular heterogeneity within a tissue. This is especially important in cancer, where tumor and tumor microenvironment heterogeneity directly impact development, maintenance, and progression of disease. While publicly available scRNA-seq cancer data sets offer unprecedented opportunity to better understand the mechanisms underlying tumor progression, metastasis, drug resistance, and immune evasion, much of the available information has been underutilized, in part, due to the lack of tools available for aggregating and analysing these data. We present CHARacterizing Tumor Subpopulations (CHARTS), a web application for exploring publicly available scRNA-seq cancer data sets in the NCBI’s Gene Expression Omnibus. More specifically, CHARTS enables the exploration of individual gene expression, cell type, malignancy-status, differentially expressed genes, and gene set enrichment results in subpopulations of cells across tumors and data sets. Along with the web application, we also make available the backend computational pipeline that was used to produce the analyses that are available for exploration in the web application. CHARTS is an easy to use, comprehensive platform for exploring single-cell subpopulations within tumors across the ever-growing collection of public scRNA-seq cancer data sets. CHARTS is freely available at charts.morgridge.org.
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DOI：
10.1126/science.aad0501
发表时间：
2016-04-08
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Tirosh I;Izar B;Prakadan SM;Wadsworth MH 2nd;Treacy D;Trombetta JJ;Rotem A;Rodman C;Lian C;Murphy G;Fallahi-Sichani M;Dutton-Regester K;Lin JR;Cohen O;Shah P;Lu D;Genshaft AS;Hughes TK;Ziegler CG;Kazer SW;Gaillard A;Kolb KE;Villani AC;Johannessen CM;Andreev AY;Van Allen EM;Bertagnolli M;Sorger PK;Sullivan RJ;Flaherty KT;Frederick DT;Jané-Valbuena J;Yoon CH;Rozenblatt-Rosen O;Shalek AK;Regev A;Garraway LA
通讯作者：
Garraway LA
CancerSEA：癌症单细胞状态图谱
影响因子：
14.9
作者：
Yuan H;Yan M;Zhang G;Liu W;Deng C;Liao G;Xu L;Luo T;Yan H;Long Z;Shi A;Zhao T;Xiao Y;Li X
通讯作者：
Li X
影响因子：
30.8
作者：
Weinstein, John N.;Collisson, Eric A.;Mills, Gordon B.;Shaw, Kenna R. Mills;Ozenberger, Brad A.;Ellrott, Kyle;Shmulevich, Ilya;Sander, Chris;Stuart, Joshua M.
通讯作者：
Stuart, Joshua M.
影响因子：
46.9
作者：
Moon, Kevin R.;van Dijk, David;Krishnaswamy, Smita
通讯作者：
Krishnaswamy, Smita
影响因子：
82.9
作者：
Laughney, Ashley M.;Hu, Jing;Massague, Joan
通讯作者：
Massague, Joan