Lotfi Slim

A systematic analysis of gene-gene interaction in multiple sclerosis

This study identifies gene-gene interactions in multiple sclerosis using GWAS data, finding 4 missense variant pairs and 117 eQTL-mediated pairs, including known interactions like GLI-I and SUFU binding.

GEPSi: A Python Library to Simulate GWAS Phenotype Data

GEPSi simulates GWAS phenotype data with biological complexity to benchmark genetic analysis methods.

Novel Methods for Epistasis Detection in Genome-Wide Association Studies

This paper introduces epiGWAS, a method for detecting epistasis in genome-wide association studies, showing improved identification of gene-gene interactions compared to existing approaches.

Nonlinear post-selection inference for genome-wide association studies

This paper introduces kernelPSI, a method for nonlinear post-selection inference in GWAS, showing it improves statistical power and interpretability compared to existing tools.