I am currently a senior bioinformatician in Achilles Therapeutics. My primary focus has been to develop an industry-grade immunotherapy/immunogenomics pipeline (based on the TRACERx pipeline pioneered from Charles Swanton’s lab) that identifies clonal neo-antigens that can elicit antitumor responses.
I completed my Bioinformatics PhD in 2017 under the co-supervision of Dr. Sohrab Shah and Dr. Christian Steidl studying tumour heterogeneity and its implications on disease progression in B-cell lymphomas. In particular, how tumour evolution plays a role in treatment resistance and how understanding this process may aid in the determination of relevant and precise therapeutic approaches for each cancer patient. Throughout my PhD and industry experience, I have acquired experience/skills in the following specific areas:
- Cancer genomic analyses that include prediction of somatic single nucleotide variants, small insertions/deletions, genomic breakpoints, gene-fusions, and copy number calling.
- Cancer evolution analyses that include the deconvolution of clonal composition, both at the single region and multi-regional level, and tracking of tumor evolution over time through serial sampling (e.g. primary vs. relapse)
- Prognostic biomarker discovery and modeling (e.g. multi-variate elastic-net Cox regression)
- Immunogenomics analyses that include HLA typing, and neo-antigen predictions
I have a passion for applying statistical and machine learning approaches to big data, in particular genomics data (e.g. sequencing data). In terms of technical skills:
- I have expertise in dealing with big data in the R programming language (e.g. data.table, tidyr, dplyr) and a thorough understanding of the core principles around R
- I have extensive experience in doing reproducible research through interactive applications and D3 web reporting (e.g. Rmarkdown, knitr, pandoc, git, shiny)
- I have expertise in developing/managing big data processing pipelines through the Make engine with experience in using ruffus, bpipe, snakemake, and nextflow.
- I have experience in continuous integration/unit testing in production based workflows.
Selected Publications [Google Scholar]
Prognostic Model to Predict Post-Autologous Stem-Cell Transplantation Outcomes in Classical Hodgkin Lymphoma
Observing Clonal Dynamics Across Spatiotemporal Axes: A Prelude to Quantitative Fitness Models for Cancer
Histological Transformation and Progression in Follicular Lymphoma: a Clonal Evolution Study
An RCOR1 loss-associated gene expression signature identifies a prognostically significant DLBCL subgroup
Recurrent somatic mutations of PTPN1 in primary mediastinal B cell lymphoma and Hodgkin lymphoma
Genomic rearrangements involving programmed death ligands are recurrent in primary mediastinal large B-cell lymphoma
Gene expression-based model using formalin-fixed paraffin-embedded biopsies predicts overall survival in advanced-stage classical Hodgkin lymphoma
An R package for generating cofeature (feature by sample) matrices. The package utilizies ggplot2::geom_tile to generate the matrix allowing for easy additions from the base matrix.
This package uses functional programming principles to iteratively run Cox regression and plot its results. The results are reported in tidy data frames. Additional utility functions are available for working with other aspects of survival analysis such as survival curves, C-statistics, etc.