Christopher M. Lalansingh

This study develops quantitative metrics and simulated datasets to evaluate subclonal reconstruction methods in tumours.

This study uses a crowdsourcing approach to stratify ALS patients, identifying four distinct clusters with unique predictors and improving outcome prediction.

HPCI is a Perl module that allows bioinformatics pipelines to run on different cluster types by abstracting cluster-specific APIs.

S22S is a reference-free method for somatic variant calling that uses genomic and population data to accurately identify SNVs without matched normal samples.

This study identifies genes driving localized and global hypermutation in tumors and finds that kataegis (localized mutation rainstorms) are associated with specific genetic alterations and patient outcomes.