BioVLAB-Cancer-Pharmacogenomics: tumor heterogeneity and pharmacogenomics analysis of multi-omics data from tumor on the cloud
- Authors
- Park, Sungjoon; Lee, Dohoon; Kim, Youngkuk; Lim, Sangsoo; Chae, Heejoon; Kim, Sun
- Issue Date
- Jan-2022
- Publisher
- OXFORD UNIV PRESS
- Citation
- BIOINFORMATICS, v.38, no.1, pp.275 - 277
- Journal Title
- BIOINFORMATICS
- Volume
- 38
- Number
- 1
- Start Page
- 275
- End Page
- 277
- URI
- https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/145951
- DOI
- 10.1093/bioinformatics/btab478
- ISSN
- 1367-4803
- Abstract
- 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.
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