Integrated genomic analysis of biological gene sets with applications in lung cancer prognosis

BMC Bioinformatics

Table 2 Counts of overlapping significant lung cancer gene sets associated with one-year survival by iTEGS, iNOTE, and GSAA

A total of 99 lung cancer associated gene sets were obtained and tested from MsigDB. Tests for iTEGS were calculated under disease-risk model specifications M: methylation effect only, G: gene expression effect only, MG: methyation and mRNA expression effects, and MGC: methylation effect, mRNA expression effect, and their interactions. The total and overlapping counts of significant gene sets identified by each method is reported here, with numbers in parentheses denoting the counts of gene sets that remain significant after Bonferroni correction at p<5×10⁻⁴

ISSN: 1471-2105