𝕋he prediction model databases only contain models that pass a stringent criteria (each family of models has its own criteria, e.g. MASHR models require at least one snp with high posterior probability of being an eQTL). Our model training algorithms are complex and conservative. Sometimes, a good … Read more →

𝕋his error usually occurs when there is a mismatch between the SNP ids used in the model and those used in the genotype file or the summary stats file. A few examples to mention; 1. Using rsids in the models against variant ids (chr_pos_ref_alt_build) in the genotype and summary stats file and vice … Read more →

ℙrediction models trained with GTEx V8 data using the cross tissue imputation approach (see UTMOST paper). Trained by Alvaro Barbeira for the paper Fine‐mapping and QTL tissue‐sharing information improves the reliability of causal gene identification Download in Zenodo here Read more →

𝔾andal et al analyzed autism spectrum disorder, schizophrenia, and bipolar disorder across multiple levels of transcriptomic organization—gene expression, local splicing, transcript isoform expression, and coexpression networks for both protein-coding and noncoding genes to produce a quantitative, … Read more →

𝕎e have recently published a new set of prediction models trained on GTEx v8 data (as part of efforts detailed in this preprint. We have overhauled the model construction, incorporating posterior inclusion probabilities and global patterns of tissue sharing, while also benefiting from larger sample … Read more →

𝔼xpression prediction models with LD reference data are available in this website. The models were trained on Common Mind Consortium, GTEx, and STARNET consortiums. The underlying algorithm is Elastic Net, informed by epigenetic data. These models were presented in “Integrative transcriptome … Read more →

𝕊ingle-tissue expression prediction models with LD reference data are available in this GitHub repository. The underlying algorithm is Elastic Net. These models were presented in “Gene expression imputation across multiple brain regions provides insights into schizophrenia risk, Huckins et al, … Read more →

𝕊ingle-tissue expression prediction models with LD reference data are available in this Zenodo repository. The underlying algorithm is Elastic Net on MESA multi-ethnic cohort. These models were presented in “Genetic architecture of gene expression traits across diverse populations”, … Read more →

𝕎e are releasing prediction models trained on GTEx Version 7 data. Download fromhere. We have updated our processing pipeline, and restricted to individuals of European ancestry to obtain more reliable LD data. This reduces false positive associations in the Summary Version of PrediXcan. Because of … Read more →

𝔼xpression prediction models with LD reference data ar available in this Zenodo repository. The underlying algorithm is Elastic Net. […] Additional support information and details are available in the Zenodo repository. You can find release notes in this link. Acknowledging these models: If … Read more →