Rehan Akbani

PCA-Plus enhances principal component analysis to better detect, visualize, and quantify batch effects and group differences in multi-omic data.

The paper compiles protein response data from cancer cell lines to drug perturbations, showing improved drug sensitivity prediction and building a protein-drug connectivity map with an accessible data portal.

OmicPioneer-sc provides an interactive visualization tool for single-cell sequencing data, integrating dimensionality reduction, heat maps, and pathway modules to aid in cell-type annotation and multi-omic analysis.

The paper develops TransPRECISE, a Bayesian network framework, to analyze pan-cancer patient and cell line interactomes, identifying pathway activities and drug sensitivities across multiple cancer types.

The paper analyzes whole-genome sequencing data from cancer samples to identify genomic footprints of telomere maintenance mechanisms, finding specific telomere variant repeat patterns associated with ATRX/DAXX mutations.

The paper examines how somatic structural variations affect TAD boundaries and gene regulation in human cancers using whole genome sequencing data.

This study identifies germline genetic variants influencing somatic mutation patterns in 2,642 cancer genomes across 39 cancer types.

This study characterizes mitochondrial genomes in 2,700 cancer patients across 37 types using whole-genome sequencing and RNA-seq, revealing mutational patterns, truncating mutations, and nuclear transfer of mitochondrial DNA.

This study analyzes chromothripsis in 2,658 cancers using whole-genome sequencing, finding it prevalent across multiple cancer types with complex structural alterations.

This study characterizes genomic, transcriptomic, and epigenomic artifacts in FFPE tissues and provides best practices to mitigate their impact on molecular analysis.