About Me
I'm a computational researcher specializing in statistical and computational genomics, currently working as a Computational Associate II at the Broad Institute of MIT and Harvard in the Claussnitzer Lab. My work centers on the genetics of cardiometabolic disease — building pipelines for genotyping, polygenic risk scoring, and LDSC heritability estimation, and using single-cell ATAC-seq to connect GWAS variants to transcription-factor activity in adipose tissue.
Before the Broad, I worked in the Sheynkman Lab at the University of Virginia on long-read proteogenomics, where I built Biosurfer, a tool for tracking how alternative splicing reshapes protein isoforms. I hold an M.S. in Computer Science from Penn State, where my thesis benchmarked long-read metagenome assembly tools.
View My Research
Research & Publications
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Peer-Reviewed Publications
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Preprints & Manuscripts in Progress
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Conference Presentations
Research Interests
GWAS
Polygenic Risk Scores
LDSC Heritability
Population Genetics
Single-Cell ATAC-seq
Cardiometabolic Disease Genetics
Biobank-Scale Analysis
Long-Read Proteogenomics
Technical Skills
Python
R
Bash
SQL
C / C++
Nextflow
Docker
Git
Terra
Galaxy
HPC Clusters
Jupyter
Publications & Presentations
2026
Genome-Wide Discovery Reveals Adipose-Specific and Systemic Regulators of Insulin Resistance
Garcia-Ureña M, Toh PJY, Martinez RS, Kaalia R, Murali M, Dashti H, et al.
medRxiv (preprint) · submitted to Nature Metabolism
2025
Biosurfer for Systematic Tracking of Regulatory Mechanisms Leading to Protein Isoform Diversity
Murali M, Saquing J, Lu S, Gao Z, Watts EF, Jordan B, Wakefield ZP, et al.
Genome Research, 35(4), 1012–1024
2025
The 9p21.3 Coronary Artery Disease Risk Locus Modulates Vascular Cell-State Transitions via Enhancer-Driven Regulation of MTAP
Audam TN, Schmandt B, Huang Y, Cho YB, Murali M, Kaalia R, Agrawal S, et al.
bioRxiv (preprint), 2025.11.18.689066
2025
Single-Nucleus DNA Accessibility Links Cardiometabolic Risk to Transcription-Factor Modules in the Adipose Lineages
Murali M, Huang Y, Perez-Schindler J, Datta S, Min B, Kaalia R, Jones TR, Dashti H, Claussnitzer M.
American Society of Human Genetics (ASHG) Annual Meeting, Boston, MA · Poster
2024
Long-Read Proteogenomics to Connect Disease-Associated sQTLs to the Protein Isoform Effectors of Disease
Abood A, Mesner LD, Jeffery ED, Murali M, Lehe M, Saquing J, Farber CR, et al.
American Journal of Human Genetics, 111(9), 1914–1931
2024
Heritability Landscape of Cardiometabolic Diseases in Human Adipocytes
Murali M, Huang Y, Datta S, Kaalia R, dosSantos F, Perez-Schindler J, Dashti H, Jones TR, Claussnitzer M.
Broad Institute Retreat, Cambridge, MA · Poster
2024
Could the Microbial-to-Host Cell Numbers in Healthy Multicellular Organisms Be Following the Golden Ratio?
Murali M, Alka G.
Current Science, 126(8), 878–881
2022
Characterization of Protein Isoform Diversity in Human Umbilical Vein Endothelial Cells via Long-Read Proteogenomics
Mehlferber MM, Jeffery ED, Saquing J, Jordan BT, … Murali M, et al.
RNA Biology, 19(1), 1228–1243
2019
Data Analytics on IoT-Based Health Monitoring System
Murali M, Bhargava M, Snehaa G, Anand A, Haque MA, Sarobin V.
International Journal of Recent Technology & Engineering (Scopus-indexed), 8(1), 220–223
2019
Low-Cost Air Sensing System
Sahoo B, Maharana A, Murali M, Shivani L, Suganya G, Premalatha M.
Proc. 3rd International Conference on Computing and Communications Technologies (ICCCT), IEEE
Manuscripts in preparation (co-author): Eliasen AU, Thorsen J, Dashti H, et al., Integration of genetic association and tissue-specific expression data reveals brain and non-brain genetic mechanisms of obesity (with M. Claussnitzer, J. Hirschhorn) · Díez-Obrero V, Svenstrup V, Smit RAJ, et al., Multi-omic gene prioritization within body-mass-index loci provides molecular insight into their variant-to-function translation.
Selected Academic Projects
Benchmarking De Novo Metagenome Assembly on Long-Read Data
M.S. thesis project: built an automated pipeline to benchmark de novo metagenome assemblers on long-read PacBio HiFi data by misassembly rate, assembly quality, and genome completeness, with contig visualization via Bandage on an HPC cluster. Advised by Prof. Mingfu Shao.
PacBio HiFi
Metagenomics
HPC
View on GitHub
FOXC1 Mouse Gene Regulation
Built a Galaxy pipeline for ChIP-exo and RNA-seq analysis to identify Forkhead Box C1 (FOXC1) binding sites in mouse stem-cell data and investigate regulation of the gene.
Galaxy
ChIP-exo
RNA-seq
k-mer Counting Methods Using Different Data Structures
Benchmarked unordered map, suffix array, hash table, and Bloom filter implementations against the KMC 2 algorithm for k-mer counting on the human GRCh38 and Staphylococcus aureus genomes, comparing memory usage and runtime.
C++
Data Structures
Genomics
