CPA: a web-based platform for consensus pathway analysis and interactive visualization.
CPA: a web-based platform for consensus pathway analysis and interactive visualization.
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DOI:
10.1093/nar/gkab421
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发表时间:
2021-07-02
影响因子:
14.9
通讯作者:
Nguyen T
中科院分区:
文献类型:
--
作者:
Nguyen H;Tran D;Galazka JM;Costes SV;Beheshti A;Petereit J;Draghici S;Nguyen T
In molecular biology and genetics, there is a large gap between the ease of data collection and our ability to extract knowledge from these data. Contributing to this gap is the fact that living organisms are complex systems whose emerging phenotypes are the results of multiple complex interactions taking place on various pathways. This demands powerful yet user-friendly pathway analysis tools to translate the now abundant high-throughput data into a better understanding of the underlying biological phenomena. Here we introduce Consensus Pathway Analysis (CPA), a web-based platform that allows researchers to (i) perform pathway analysis using eight established methods (GSEA, GSA, FGSEA, PADOG, Impact Analysis, ORA/Webgestalt, KS-test, Wilcox-test), (ii) perform meta-analysis of multiple datasets, (iii) combine methods and datasets to accurately identify the impacted pathways underlying the studied condition and (iv) interactively explore impacted pathways, and browse relationships between pathways and genes. The platform supports three types of input: (i) a list of differentially expressed genes, (ii) genes and fold changes and (iii) an expression matrix. It also allows users to import data from NCBI GEO. The CPA platform currently supports the analysis of multiple organisms using KEGG and Gene Ontology, and it is freely available at http://cpa.tinnguyen-lab.com. Pathway analysis and visualization using consensus pathway analysis (CPA). CPA allows users to compare, contrast and combine analysis results across different methods and experiments, and supports over 1000 organisms.
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影响因子:
14.9
作者:
Gene Ontology Consortium
通讯作者:
Gene Ontology Consortium
影响因子:
14.9
作者:
Kuleshov MV;Jones MR;Rouillard AD;Fernandez NF;Duan Q;Wang Z;Koplev S;Jenkins SL;Jagodnik KM;Lachmann A;McDermott MG;Monteiro CD;Gundersen GW;Ma'ayan A
通讯作者:
Ma'ayan A
影响因子:
5.8
作者:
Gu, Zuguang;Wang, Jin
通讯作者:
Wang, Jin
影响因子:
5.8
作者:
Al-Shahrour, F;Díaz-Uriarte, R;Dopazo, J
通讯作者:
Dopazo, J
DOI:
10.1111/j.2517-6161.1995.tb02031.x
发表时间:
1995-01-01
影响因子:
5.8
作者:
BENJAMINI, Y;HOCHBERG, Y
通讯作者:
HOCHBERG, Y