3 papers
q-bio.GN2022
rfPhen2Gen: A machine learning based association study of brain imaging phenotypes to genotypes
Muhammad Ammar Malik, Alexander S. Lundervold, Tom Michoel
Imaging genetic studies aim to find associations between genetic variants and imaging quantitative traits. Traditional genome-wide association studies (GWAS) are based on univariat…
q-bio.GN2021
High-dimensional multi-trait GWAS by reverse prediction of genotypes
Muhammad Ammar Malik, Adriaan-Alexander Ludl, Tom Michoel
Multi-trait genome-wide association studies (GWAS) use multi-variate statistical methods to identify associations between genetic variants and multiple correlated traits simultaneo…
stat.ME2020
Restricted maximum-likelihood method for learning latent variance components in gene expression data with known and unknown confounders
Muhammad Ammar Malik, Tom Michoel
Random effect models are popular statistical models for detecting and correcting spurious sample correlations due to hidden confounders in genome-wide gene expression data. In appl…