Deshan Perera

Apollo: A comprehensive GPU-powered within-host simulator for viral evolution and infection dynamics across population, tissue, and cell

Apollo simulates within-host viral evolution and infection dynamics, validating limitations of transmission inference tools using HIV cohort data.

Enhancing Disease Risk Gene Discovery by Integrating Transcription Factor-Linked Trans-located Variants into Transcriptome-Wide Association Analyses

This study introduces transTF-TWAS, a method that integrates transcription factor-linked trans-located variants into transcriptome-wide association analyses to improve disease risk gene discovery.

cLD: Rare-variant disequilibrium between genomic regions identifies novel genomic interactions

The paper introduces cLD, a statistic for measuring rare-variant linkage disequilibrium between genomic regions, and shows it identifies novel genomic interactions and associations.

Tissue-specific transfer-learning enables retasking of a general comprehensive model to a specific domain

The paper applies transfer learning to adapt a general-purpose model to a specific domain using limited data, demonstrating improved performance in breast cancer-related tasks.

CATE: A fast and scalable CUDA implementation to conduct highly parallelized evolutionary tests on large scale genomic data.

CATE accelerates evolutionary genomic tests using GPU and CPU parallelization, achieving over 180x speedup compared to standard tools.

Statistical model integrating interactions into genotype-phenotype association mapping: an application to reveal 3D-genetic basis underlying Autism

The paper introduces ILMM, a statistical model that integrates genetic interactions into genotype-phenotype association mapping, revealing 3D-genetic basis of ASD and 3D-eQTLs using whole genome and transcriptome sequencing data.

Reconstruction of microbial haplotypes by integration of statistical and physical linkage in scaffolding

PoolHapX reconstructs microbial haplotypes by integrating genetic sharing and genomic sequencing, outperforming existing tools and revealing new insights into HIV evolution.