LungGENIE: the lung gene-expression and network imputation engine.

ABSTRACT:

Background

Few cohorts have study populations large enough to conduct molecular analysis of ex vivo lung tissue for genomic analyses. Transcriptome imputation is a non-invasive alternative with many potential applications. We present a novel transcriptome-imputation method called the Lung Gene Expression and Network Imputation Engine (LungGENIE) that uses principal components from blood gene-expression levels in a linear regression model to predict lung tissue-specific gene-expression.

Methods

We use paired blood and lung RNA sequencing data from the Genotype-Tissue Expression (GTEx) project to train LungGENIE models. We replicate model performance in a unique dataset, where we generated RNA sequencing data from paired lung and blood samples available through the SUNY Upstat

SUBMITTER: Ghosh AJ 

PROVIDER: S-EPMC11892309 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature