Efficient Data Mining Analysis of Genomics and Clinical Data for Pharmacogenomics Applications

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• 关键词：Genotyping microarrays ; ADME genes ; Pharmacogenomics ; Overall survival ; Progression ; free survival
• 刊名：Lecture Notes in Computer Science
• 出版年：2017
• 出版时间：2017
• 年：2017
• 卷：10147
• 期：1
• 页码：239-248
• 丛书名：Fuzzy Logic and Soft Computing Applications
• ISBN：978-3-319-52962-2
• 卷排序：10147

文摘

The identification of biomarkers for the estimation of cancer patients’ survival is a crucial problem in oncology. The Affymetrix DMET microarray platform allows to determine the ADME gene variants of a patient and to correlate them with drug-dependent adverse events. We present a bioinformatics tool devoted to the discovery of gene variants correlated to a different response of cancer patients to drugs and able to compute the overall survival (OS) and progression-free survival (PFS) of cancer patients. The tool is based on the integration of DMET-Miner and OSAnalyzer. DMET-Miner is a data mining tool able to extract Association Rules from DMET datasets and OSAnalyzer is a software tool able to perform an automatic analysis of DMET data enriched with survival events. After presenting DMET-Miner and OSAnalyzer, we discuss a case study to highlight the usefulness of the pipeline constituted by DMET-Miner and OSAnalyzer when analyzing a large cohort of patients.