Identifying Glioblastoma Gene Networks Based on Hypergeometric Test Analysis

ABSTRACT: Patient specific therapy is emerging as an important possibility for many cancer patients. However, to identify such therapies it is essential to determine the genomic and transcriptional alterations present in one tumor relative to control samples. This presents a challenge since use of a single sample precludes many standard statistical analysis techniques. We reasoned that one means of addressing this issue is by comparing transcriptional changes in one tumor with those observed in a large cohort of patients analyzed by The Cancer Genome Atlas (TCGA). To test this directly, we devised a bioinformatics pipeline to identify differentially expressed genes in tumors resected from patients suffering from the most common malignant adult brain tumor, glioblastoma (GBM). We performed RNA se

ORGANISM(S): Homo sapiens

SUBMITTER: Nagi Ayad 

PROVIDER: E-GEOD-62731 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress