Evaluating the consistency of large-scale pharmacogenomic studies

Raziur Rahman, Saugato Rahman Dhruba, Kevin Matlock, Carlos De-Niz, Souparno Ghosh, Ranadip Pal

Research output: Contribution to journalReview articlepeer-review

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.

Original languageEnglish
Pages (from-to)1734-1753
Number of pages20
JournalBriefings in Bioinformatics
Volume20
Issue number5
DOIs
StatePublished - Sep 27 2019

Keywords

  • copulas
  • database dependencies
  • pairwise relationships
  • pharmacogenomic databases

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