Bio

I am currently a Postdoctoral Researcher in the Smyth Lab at the Walter and Eliza Hall Institute of Medical Research. At the WEHI, most of my research has been focused on the analysis and interpretation of bulk and single-cell epigenomic, transcriptomic, and proteomics data. I enjoy developing new statistical methods and writing efficient bioinformatic tools that can help researchers make sense of their data.

In 2020, I graduated with a PhD in biostatistics from the University of North Carolina at Chapel Hill. During my PhD, I developed statistical methods for the analysis of both bulk and single-cell epigenomic assays. At UNC, I was a graduate researcher in the Hispanic Community Health Study / Study of Latinos (HCHS/SOL) and developed/applied statistical methods to analyze data from the HCHS/SOL under complex survey design settings.

Projects

• catchSalmon/catchKallisto (within edgeR)
  • Estimation of mapping ambiguity overdispersion from transcript quantification of short read RNA-seq data. It unlocks uncertainty-free differential expression assessment at the transcript-level within edgeR.
  • R/Bioconductor
  • Workflow and User’s Guide
  • Paper
• epigraHMM
  • A toolkit for the analysis of epigenomic datasets such as ChIP-seq, ATAC-seq, CUT&RUN, and CUT&Tag. It performs differential and consensus peak calling from multi-sample multi-condition datasets.
  • R/Bioconductor
  • Vignette
  • Paper
• ZIMHMM
  • A consensus peak caller for epigenomic datasets. It implements a fast hidden Markov model with mixed-effects zero-inflated negative binomial emissions using sample-specific random effects.
  • GitHub
  • Paper

Timeline