- Link to my current CV (Aug 2021)
- Link to my publications on NCBI
- Link to my dissertation on Texas ScholarWorks
Single Cell Epigenomics at the Gene Regulation ObservatoryI only recently moved into this new role, but I'll be updating this space frequently with wet-lab and computational efforts.
Functional Genomics: Cardiovascular GeneticsIn the Ellinor laboratory, I worked on a variety of projects, many of which are now being published! Many of these projects also have results viewable at the Broad Cardiovascular Disease knowledge portal. A selection of publications in which I've been involved include:
- Rare Coding Variants Associated With Electrocardiographic Intervals Identify Monogenic Arrhythmia Susceptibility Genes: A Multi-Ancestry Analysis
- Epigenetic maps of chromatin states in healthy human left atrial tissue
- Genetic determinants of P-wave duration (conduction through the atria)
- A very large GWAS for the PR interval (measures conduction through the AV node)
- A massive single nucleus RNA-seq study of the healthy human heart
- Monogenic and polygenic contributions to AF risk
- Pitx2c promoter-enhancer interactions and AF (with Jim Martin's lab)
BioinformaticsIn October 2020, I was fortunate to be able to do two primers for the Medical and Population Genetics group at the Broad Institute on bulk RNA-sequencing best practices! Youtube videos are linked below:
- A Practical Guide To Differential Gene Expression and Pathway Analysis
- Using tximport and DEseq2 to identify differentially expressed genes: Terra tutorial
During the Fall of 2019, and over the first half of 2020, I informally taught a course on computational biology (link requires a Broad email address to access). During those sessions, we covered the following topics (links are to overview PDFs, you can use these if you credit me!):
- Big data and genomics
- single cell RNA-seq analysis using ScanPy, including subclustering
- Including using Jupyer notebooks on Terra
- History of single cell genomics
- An overview of a script I wrote to demonstrate analysis of single cell data
- Pathway enrichment & bulk RNA-seq
- Bulk RNA-seq analysis using R
- The link above is to a Terra notebook, access should be open (requires gmail address)
- I walk through this notebook in the youtube link above!
Functional Genomics: Glioblastoma multiformeIn the Iyer lab, I worked on several projects that relate to the genomics of glioblastoma multiforme (GBM).
The culmination of my work there was to profile histone PTMs in several primary GBM lesions. We also did RNA-seq from these same samples, and found that common bivalent chromatin state regions (marked by active and repressive histone PTMs at the same locus) revealed a striking enrichment for genes involved in GBM "stemness" which is thought to relate to the strong reistant GBM has to most chemotherapies. We also found that enhancers and bivalent regions clustered based on their gene expression based molecular subtype, with proneural samples forming a group, and classical/mesenchymal samples forming a second group.
In my other work during graduate school, I worked on quantifying allele specific bias in ChIP-seq. I also participated in an eQTL analysis of the GBM genome, derived from array data. In my first foray into atrial fibrillation, I did some selective genotyping of individuals undergoing cardiac ablation for treatment of AF.
Finally, I continued to work with the Aldrich laboratory, and we did some really cool studies of amino acid conservation across many phyla for the highly conserved calcium signaling protein calmodulin.