TOPMed MESA multi-ancestry transcriptome prediction models

This Zenodo file collection includes three developed transcriptome prediciton models with funtionally informed variants (FIVs) by using TOPMed MESA multi-ancestry participants with TOPMed Freeze 8 whole-genome sequencing (WGS) data and RNA-seq data from peripheral blood mononuclear cells (PBMCs). These prediction models can be used for transcriptome-wide association study (TWAS) analysis by integrating with GWAS summary statistics. EN-FM: Elastic Net with Fine-Mapped variants. To run EN model on fine-mapped variants, we follow code provided in PrediXcan Github (https://github.com/hakyimlab/PredictDB_Pipeline_GTEx_v7/tree/master/model_training). PUMICE: Prediction Using Models Informed by Chromatin conformation and Epigenomics; 3D genomic data and epigenomic annotation from EBV-transformed lymphocytes were used to construct PUMICE models. To run PUMICE model, we follow code provided in PUMICE Github (https://github.com/ckhunsr1/PUMICE). PUMICE-FM: PUMICE with Fine-Mapped variants. To run PUMICE model on fine-mapped variants, we also follow code provided in PUMICE Github (https://github.com/ckhunsr1/PUMICE). The maunscript is under review. The preprint is here https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5194962.