sjessa Goto Github PK

• I'm a post-doc based jointly in Dr. Anshul Kundaje's lab and Dr. Will Greenleaf's lab in the Department of Genetics at Stanford University
• I did my PhD in Quantitative Life Sciences in Dr. Claudia Kleinman's lab at McGill University, where I used integrative computational analyses of omics data types to answer biological questions about cell identity, cell fate, and gene regulation in brain development and brain cancer
• 🧬 I care about bioinformatics/computational biology research that emphasizes reproducibility, transparency, and reusability
• 📖 Find my papers on Google Scholar and find me on LinkedIn

Here are the key research projects I worked on during my PhD:

We assembled a scRNAseq reference dataset of >100k cells from nine timepoints in the developing mouse brain to profile cell types and their expression patterns and dynamics.

• Stalled developmental programs at the root of pediatric brain tumors, Jessa et al, Nature Genetics, 2019
• 📦 cytobox, R package for scRNAseq data visualization
• braindex, custom interactive data portal implemented in R Shiny
• braindex source code

Leveraging our brain reference atlas, we designed approaches to computationally integrate primary patient tumor omics data (scRNAseq, scATACseq, bulk RNAseq, ChIPseq, HiC) with the atlas in order to identify, for each subtype of pediatric brain tumors, their most likely cell-of-origin.

• Stalled developmental programs at the root of pediatric brain tumors, Jessa et al, Nature Genetics, 2019
• Histone H3.3G34-mutant interneuron progenitors co-opt PDGFRA for gliomagenesis, Chen*, Deshmukh*, Jessa* et al, Cell, 2020
  • G34-gliomas, the code & analysis for my contributions to the Chen et al study
• K27M in canonical and noncanonical H3 variants occurs in distinct oligodendroglial cell lineages in brain midline gliomas, Jessa*, Mohammadnia*, Harutyunyan*, et al, Nature Genetics, 2022
  • HGG-oncohistones, the the code & analysis for the H3K27M gliomas study