Identifying candidate diagnostic markers for early stage of non-small cell lung cancer.

ABSTRACT: We performed a series of bioinformatics analysis on a set of important gene expression data with 76 samples in early stage of non-small cell lung cancer, including 40 adenocarcinoma samples, 16 squamous cell carcinoma samples and 20 normal samples. In order to identify the specific markers for diagnosis, we compared the two subtypes with the normal samples respectively to determine the gene expression characteristics. Through the multi-dimensional scaling classification, we found that the samples were clustered well according to the disease cases. Based on the classification results and using empirical Bayes moderation and treat method, 486 important genes associated with the disease were identified. We constructed gene functions and gene pathways to verify our result and explain the patho

SUBMITTER: Wu Z 

PROVIDER: S-EPMC6855900 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature