TcellInflamedDetector: an R package to distinguish T cell inflamed tumor types from non–T cell inflamed tumor types
- 주제(키워드) gene expression , immune checkpoint inhibitors , immunotherapy , prognosis , RNA-seq , software
- 관리정보기술 faculty
- 등재 SCOPUS
- 발행기관 Korea Genome Organization
- 발행년도 2022
- 총서유형 Journal
- URI http://www.dcollection.net/handler/ewha/000000191073
- 본문언어 영어
- Published As https://doi.org/10.5808/gi.22005
초록/요약
A major issue in the use of immune checkpoint inhibitors is their lack of efficacy in many patients. Previous studies have reported that the T cell inflamed signature can help predict the response to immunotherapy. Thus, many studies have investigated mechanisms of im-munotherapy resistance by defining the tumor microenvironment based on T cell inflamed and non–T cell inflamed subsets. Although methods of calculating T cell inflamed subsets have been developed, valid screening tools for distinguishing T cell inflamed from non–T cell inflamed subsets using gene expression data are still needed, since general researchers who are unfamiliar with the details of the equations can experience difficulties using ex-tant scoring formulas to conduct analyses. Thus, we introduce TcellInflamedDetector, an R package for distinguishing T cell inflamed from non–T cell inflamed samples using cancer gene expression data via bulk RNA sequencing. © 2022 Korea Genome Organization.
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