7 papers
EFGPP: Exploratory framework for genotype-phenotype prediction
Muhammad Muneeb, David B. Ascher
Predicting complex human traits from genetic data is challenging because different genetic, clinical, and molecular data sources often contain different parts of the signal. Here,…
PhenotypeToGeneDownloaderR: automated multi-source retrieval and validation of phenotype-associated genes
Muhammad Muneeb, David B. Ascher
Identifying phenotype-associated genes is a common first step in polygenic risk score construction, enrichment testing, target prioritisation and variant interpretation, but releva…
Benchmarking end-to-end genotype-to-phenotype prediction workflows across 80 openSNP phenotypes
Muhammad Muneeb, David B. Ascher, YooChan Myung +2
Genotype-to-phenotype prediction is a central goal of statistical genetics, yet practical comparisons of prediction workflows remain limited in small, heterogeneous, participant-sh…
A harmonized benchmarking framework for implementation-aware evaluation of 46 polygenic risk score tools across binary and continuous phenotypes
Muhammad Muneeb, David B. Ascher
Polygenic risk score (PRS) tools differ substantially in statistical assumptions, input requirements, and implementation complexity, making direct comparison difficult. We develope…
G2DR: A Genotype-First Framework for Genetics-Informed Target Prioritization and Drug Repurposing
Muhammad Muneeb, David B. Ascher
Human genetics offers a promising route to therapeutic discovery, yet practical frameworks translating genotype-derived signal into ranked target and drug hypotheses remain limited…
Identifying genes associated with phenotypes using machine and deep learning
Muhammad Muneeb, David B. Ascher, YooChan Myung
Identifying disease-associated genes enables the development of precision medicine and the understanding of biological processes. Genome-wide association studies (GWAS), gene expre…