Ontology highlight
ABSTRACT: Background
Cervical cancer is the fourth common cancer among women. Its prognosis needs our more attention. Our purpose was to identity new prognostic gene sets to help other researchers develop more effective treatment for cervical cancer patients and improve the prognosis of patients.Methods
We used gene set variation analysis (GSVA) to calculate the enrichment scores of gene sets and identified three subtypes of cervical cancer through the Cox regression model, k-means clustering algorithm, and nonnegative matrix factorization method (NMF). Chi-square test was utilized to test whether a certain clinical characteristic is different among divided subtypes. We further screened the prognostic gene sets using differential analysis, univariate Cox regression analysis, and leas
SUBMITTER: Zhong Z
PROVIDER: S-EPMC9588340 | biostudies-literature | 2022
REPOSITORIES: biostudies-literature