Blar i Department of Informatics på forfatter "Malik, Muhammad Ammar"
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Machine learning approaches for high-dimensional genome-wide association studies
Malik, Muhammad Ammar (Doctoral thesis, 2022-08-24)Formålet med Genome-wide association studies (GWAS) er å finne statistiske sammenhenger mellom genetiske varianter og egenskaper av interesser. De genetiske variantene som forklarer mye av variasjonene i genomfattende ... -
Restricted maximum-likelihood method for learning latent variance components in gene expression data with known and unknown confounders
Malik, Muhammad Ammar; Michoel, Tom (Journal article; Peer reviewed, 2022)Random effects models are popular statistical models for detecting and correcting spurious sample correlations due to hidden confounders in genome-wide gene expression data. In applications where some confounding factors ...