The dChip survival analysis module for microarray data

Background: Genome-wide expression signatures are emerging as potential marker for overall survival and disease recurrence risk as evidenced by recent commercialization of gene expression based biomarkers in breast cancer. Similar predictions have recently been carried out using genome-wide copy number alterations and microRNAs. Existing software packages for microarray data analysis provide functions to define expression-based survival gene signatures. However, there is no software that can perform survival analysis using SNP array data or draw survival curves interactively for expression-based sample clusters. Results: We have developed the survival analysis module in the dChip software that performs survival analysis across the genome for gene expression and copy number microarray data. Built on the current dChip software’s microarray analysis functions such as chromosome display and clustering, the new survival functions include interactive exploring of Kaplan-Meier (K-M) plots ...

• Type: Journal
• Year: 2011
• Where: BMCBI
• Authors: Samir B. Amin, Parantu K. Shah, Aimin Yan, Sophia Adamia, Stephane Minvielle, Herve Avet-Loiseau, Nikhil C. Munshi, Cheng Li
• Keywords: Artificial Intelligence, BMCBI 2011, Expression-based Survival Gene, Survival Analysis, Survival Analysis Module