REALGAR: a web app of integrated respiratory omics data.

ABSTRACT:

Motivation

In the post genome-wide association study (GWAS) era, omics techniques have characterized information beyond genomic variants to include cell and tissue type-specific gene transcription, transcription factor binding sites, expression quantitative trait loci (eQTL) and many other biological layers. Analysis of omics data and its integration has in turn improved the functional interpretation of disease-associated genetic variants. Over 170 000 transcriptomic and epigenomic datasets corresponding to studies of various cell and tissue types under specific disease, treatment and exposure conditions are available in the Gene Expression Omnibus resource. Although these datasets are valuable to guide the design of experimental validation studies to understand the function of dis

SUBMITTER: Kan M 

PROVIDER: S-EPMC9477519 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature