Independent component analysis of cancer transcriptomes: optimization of parameters and improvement of interpretability

M. Chepeleva, A. Kakoichankava, M. M. Yatskou, P. V. Nazarov

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Here we estimated the optimal parameters of the independent component analysis method regarding the tasks of identification of glioblastoma and pancreatic cancer subtypes, prediction of patient survival and characterization of active biological processes. Analysis of deconvolution results of bulk and single-cell data allows sharing annotation between highly correlated components and improving interpretability of the results
Original languageEnglish
Title of host publicationComputer Technologies and Data Analysis (CTDA'2020) : Materials of II International Scientific-Practical Conference, Minsk, 23-24 April, 2020
EditorsV.A. Bishkek, V. Skakun
Place of PublicationMinsk
PublisherBSU
Pages170-173
Number of pages4
ISBN (Print)978-985-566-942-6.
Publication statusPublished - 9 Jul 2020

Keywords

  • transcriptomics; RNA-seq; independent component analysis; single-cell; cancer; survival

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