Organ-specific prioritization and annotation of non-coding regulatory variants in the human genome
Year: 2023
Type: article
Abstract: Data to reproduce analyses in the manuscript. GWAS predictions of TLand models. Please see Fig1a to determine which model to use: We defined organs with >=100 available ChIP-seq assays as “high data availability” and those with <100 assays as “low data availability”. We observed that the TLand (full) model consistently outperformed the TLand light model in organs with high data availability (Fig 1a and c; Supplementary Fig 5), while the light model surpassed the full model in organs with low data availability. For example, the organ-specific TLand light model was the best model when holding out the embryo organ (AUPR 0.639, AUROC 0.774). Those findings indicate that TLand light models are suitable for predicting regulatory variants for organs with low data availability while TLand (full) models are more suitable for organs with high data availability.
Authors: Nanxiang Zhao, Sherpa, Rintsen Norbu, Shengcheng Dong, Howcroft, Kobe, Alan Boyle
Institutions: University of Michigan, Stanford University
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W6969068705