CHARTS: a web application for characterizing and comparing tumor subpopulations in publicly available single-cell RNA-seq data sets
Autor: | Matthew N. Bernstein, Mark E. Burkard, Zijian Ni, Michael Collins, Ron Stewart, Christina Kendziorski |
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Jazyk: | angličtina |
Rok vydání: | 2021 |
Předmět: |
Computer science
Cell RNA-Seq Drug resistance Computational biology lcsh:Computer applications to medicine. Medical informatics Biochemistry Metastasis Set (abstract data type) 03 medical and health sciences 0302 clinical medicine Structural Biology Neoplasms Gene expression Tumor Microenvironment medicine Humans Profiling (information science) Web application Molecular Biology Gene lcsh:QH301-705.5 030304 developmental biology 0303 health sciences Tumor microenvironment Sequence Analysis RNA business.industry Gene Expression Profiling Applied Mathematics Cancer medicine.disease Computer Science Applications medicine.anatomical_structure lcsh:Biology (General) Tumor progression 030220 oncology & carcinogenesis lcsh:R858-859.7 Single-Cell Analysis DNA microarray business Software |
Zdroj: | BMC Bioinformatics, Vol 22, Iss 1, Pp 1-9 (2021) BMC Bioinformatics |
ISSN: | 1471-2105 |
Popis: | Background 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. Results 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. Conclusion 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. |
Databáze: | OpenAIRE |
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