Drug/Cell-line Browser: interactive canvas visualization of cancer drug/cell-line viability assay datasets
Author(s) -
Qiaonan Duan,
Zichen Wang,
Nicolas Fernandez,
Andrew D. Rouillard,
Christopher M. Tan,
Cyril H. Benes,
Avi Ma’ayan
Publication year - 2014
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btu526
Subject(s) - drug , cancer cell lines , visualization , line (geometry) , cell culture , computer science , viability assay , drug response , cell , cancer drugs , computational biology , cancer , biology , cancer cell , data mining , pharmacology , biochemistry , genetics , geometry , mathematics
Recently, several high profile studies collected cell viability data from panels of cancer cell lines treated with many drugs applied at different concentrations. Such drug sensitivity data for cancer cell lines provide suggestive treatments for different types and subtypes of cancer. Visualization of these datasets can reveal patterns that may not be obvious by examining the data without such efforts. Here we introduce Drug/Cell-line Browser (DCB), an online interactive HTML5 data visualization tool for interacting with three of the recently published datasets of cancer cell lines/drug-viability studies. DCB uses clustering and canvas visualization of the drugs and the cell lines, as well as a bar graph that summarizes drug effectiveness for the tissue of origin or the cancer subtypes for single or multiple drugs. DCB can help in understanding drug response patterns and prioritizing drug/cancer cell line interactions by tissue of origin or cancer subtype.
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