Identifying and analyzing different cancer subtypes using RNA-seq data of blood platelets.

ABSTRACT: Detection and diagnosis of cancer are especially important for early prevention and effective treatments. Traditional methods of cancer detection are usually time-consuming and expensive. Liquid biopsy, a newly proposed noninvasive detection approach, can promote the accuracy and decrease the cost of detection according to a personalized expression profile. However, few studies have been performed to analyze this type of data, which can promote more effective methods for detection of different cancer subtypes. In this study, we applied some reliable machine learning algorithms to analyze data retrieved from patients who had one of six cancer subtypes (breast cancer, colorectal cancer, glioblastoma, hepatobiliary cancer, lung cancer and pancreatic cancer) as well as healthy persons. Quantit

SUBMITTER: Zhang YH 

PROVIDER: S-EPMC5675649 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature