Evaluating the consistency of large-scale pharmacogenomic studies. (31st May 2019)

• Record Type: Journal Article
• Authors: Rahman, Raziur; Dhruba, Saugato Rahman; Matlock, Kevin; De-Niz, Carlos; Ghosh, Souparno; Pal, Ranadip
• Is Part Of: Briefings in bioinformatics. Volume 20:Number 5(2020)
• Page Start: 1734
• Page End: 1753
• Publication Date: 2019-05-31
• Subjects: pharmacogenomic databases -- database dependencies -- copulas -- pairwise relationships; Genetics -- Data processing -- Periodicals; Molecular biology -- Data processing -- Periodicals; Genomes -- Data processing -- Periodicals; 572.80285
• DOI: 10.1093/bib/bby046
• Languages: English
• ISSNs: 1467-5463

Abstract

Abstract: Recent years have seen an increase in the availability of pharmacogenomic databases such as Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Cell Line Encyclopedia (CCLE) that provide genomic and functional characterization information for multiple cell lines. Studies have alluded to the fact that specific characterizations may be inconsistent between different databases. Analysis of the potential discrepancies in the different databases is highly significant, as these sources are frequently used to analyze and validate methodologies for personalized cancer therapies. In this article, we review the recent developments in investigating the correspondence between different pharmacogenomics databases and discuss the potential factors that require attention when incorporating these sources in any modeling analysis. Furthermore, we explored the consistency among these databases using copulas that can capture nonlinear dependencies between two sets of data.