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Q-omics: Smart Software for Assisting Oncology and Cancer Research

Authors :
Youngju Kim
Euna Jeong
Sumin Jeong
Heeseung Yoo
Sukjoon Yoon
Ji-Eun Lee
Seonghee Jin
Source :
Molecules and Cells
Publication Year :
2021
Publisher :
Korean Society for Molecular and Cellular Biology, 2021.

Abstract

The rapid increase in collateral omics and phenotypic data has enabled data-driven studies for the fast discovery of cancer targets and biomarkers. Thus, it is necessary to develop convenient tools for general oncologists and cancer scientists to carry out customized data mining without computational expertise. For this purpose, we developed innovative software that enables user-driven analyses assisted by knowledge-based smart systems. Publicly available data on mutations, gene expression, patient survival, immune score, drug screening and RNAi screening were integrated from the TCGA, GDSC, CCLE, NCI, and DepMap databases. The optimal selection of samples and other filtering options were guided by the smart function of the software for data mining and visualization on Kaplan-Meier plots, box plots and scatter plots of publication quality. We implemented unique algorithms for both data mining and visualization, thus simplifying and accelerating user-driven discovery activities on large multiomics datasets. The present Q-omics software program (v0.95) is available at http://qomics.sookmyung.ac.kr.

Details

ISSN :
02191032
Volume :
44
Database :
OpenAIRE
Journal :
Molecules and Cells
Accession number :
edsair.doi.dedup.....a9a65917a93444ef0111eb36fe4135cd
Full Text :
https://doi.org/10.14348/molcells.2021.0169