Matthew Ritchie-Lab team

Matthew Ritchie-Lab team



My team collaborates closely with the Blewitt, Asselin-Labat, Naik, and Smyth laboratories at the institute. We use and develop advanced computational algorithms to analyse genome-wide data.
We welcome enquiries from individuals with a computational background (statistics, mathematics, computer science) interested in applying their skills to medical research.

Charity Law, Postdoctoral Scientist, BSc(Hons) PhD Melbourne 
Key Publication: Law CW, Chen Y, Shi W, Smyth GK. voom: Precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol. 2014;15(2):R29. PMID: 24485249

Cynthia Liu, Computational Scientist, BSc(Hons) Melbourne
Key Publication: Liu R, Dai Z, Yeager M, Irizarry RA, Ritchie ME. KRLMM: an adaptive genotype calling method for common and low frequency variants. BMC Bioinformatics. 2014;15:158. PMID: 24886250.

Jenny Dai, Computational Scientist, BSc Melbourne
Key Publication: Dai Z, Sheridan JM, Gearing LJ, Moore DL, Su S, Wormald S, Wilcox S, O'Connor L, Dickins RA, Blewitt ME, Ritchie ME. edgeR: a versatile tool for the analysis of shRNA-seq and CRISPR-Cas9 genetic screens. F1000Res. 2014;3:95. PMID: 24860646.

Shian Su, Undergraduate Student
Key Publication: Liu R, Holik AZ, Su S, Jansz N, Chen K, Leong HS, Blewitt ME, Asselin-Labat ML, Smyth GK, Ritchie ME. Why weight? Modelling sample and observational level variability improves power in RNA-seq analyses. Nucleic Acids Res. 2015;43(15):e97. PMID: 25925576.

Luyi Tian, Masters Student, BSc China

Alexis Lucattini, Masters Student, BSc Melbourne