Senior Research Scientist
My lab and I develop and apply multivariate statistical methods and machine learning to the analysis of high-throughput whole genome data arising from molecular and genomic studies of cancer, with a particular focus on meta analysis and development of models that integrate of multiple sources of data. My research is applied to understanding;
- the molecular heterogeneity of tumor subtypes
- the role of the cancer microenvironment in disease progression and drug resistance
R/Bioconductor packages developed in our lab includes;
mogsa An R/Bioconductor developed by Chen Meng with Azfar Basunia for matrix decomposition for integrating multiple ‘omics datasets (includes MCIA, CPCA, MFA) and extracting single sample gene set scores of the integrated datasets (when the multiple ‘omics data were generated on the same cases/samples). .
iBBiG An R/Bioconductor developed by Dan Gusenleitner for biclustering of binary data. Designed for finding clusters (modules) in matrixes of discretized p-values (from single sample Gene Set analysis).
omicade4 An R/Bioconductor developed by Chen Meng for matrix decomposition of multiple ‘omics datasets (includes MCIA, etc). An extension of ade4.
made4 An R/Bioconductor package (thats pretty old now) for matrix decompostion (PCA, COA) and clustering of gene expression data. An extension of ade4
survcomp An R/Bioconductor package developed by Markus Schroeder together with Benjamin Haibe-Kains for survival analysis (includes c-index)
RamiGO An R/Bioconductor package developed by Markus Schroeder that calls AmiGO to visualize, retrieving DAG GO trees.
BSc 1994 University of Limerick, Ireland
PhD. 2000 University of Manchester, UK