GCclassifier: an R package for the prediction of molecular subtypes of gastric cancer
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AbstractGastric cancer (GC) is one of the most commonly diagnosed malignancies, threatening millions of lives worldwide each year. Importantly, GC is a heterogeneous disease, posing a significant challenge to the selection of patients for more optimized therapy. Over the last decades, extensive community effort has been spent on dissecting the heterogeneity of GC, leading to the identification of distinct molecular subtypes that are clinically relevant. However, so far, no tool is publicly available for GC subtype prediction, hindering the research into GC subtype-specific biological mechanisms, the design of novel targeted agents, and potential clinical applications. To address the unmet need, we developed an R package GCclassifier for predicting GC molecular subtypes based on gene expression profiles. To facilitate the use by non-bioinformaticians, we also provide an interactive, user-friendly web server implementing the major functionalities of GCclassifier. The predictive performance of GCclassifier was demonstrated using case studies on multiple independent datasets.
Acceptance Date15/01/2024
All Author(s) ListJiang Li, Lingli He, Xianrui Zhang, Xiang Li, Lishi Wang, Zhongxu Zhu, Kai Song, Xin Wang
Journal nameComputational and Structural Biotechnology Journal
Year2024
Month12
Volume Number23
PublisherElsevier
Pages752 - 758
ISSN2001-0370
LanguagesEnglish-United States
KeywordsCancer subtyping, GCclassifier, Gastric cancer, R package, Shiny application

Last updated on 2024-19-09 at 12:40