BioVLAB-Cancer-Pharmacogenomics: tumor heterogeneity and pharmacogenomics analysis of multi-omics data from tumor on the cloud

Sungjoon Park, Dohoon Lee, Youngkuk Kim, Sangsoo Lim, Heejoon Chae, Sun Kim

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Motivation: Multi-omics data in molecular biology has accumulated rapidly over the years. Such data contains valuable information for research in medicine and drug discovery. Unfortunately, data-driven research in medicine and drug discovery is challenging for a majority of small research labs due to the large volume of data and the complexity of analysis pipeline. Results: We present BioVLAB-Cancer-Pharmacogenomics, a bioinformatics system that facilitates analysis of multi-omics data from breast cancer to analyze and investigate intratumor heterogeneity and pharmacogenomics on Amazon Web Services. Our system takes multi-omics data as input to perform tumor heterogeneity analysis in terms of TCGA data and deconvolve-and-match the tumor gene expression to cell line data in CCLE using DNA methylation profiles. We believe that our system can help small research labs perform analysis of tumor multi-omics without worrying about computational infrastructure and maintenance of databases and tools.

Original languageEnglish
Pages (from-to)275-277
Number of pages3
JournalBioinformatics
Volume38
Issue number1
DOIs
StatePublished - 1 Jan 2022

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