GenoExp

GenoExp predicts gene expression levels from single nucleotide polymorphisms (SNPs) to quantify SNP-driven expression variability across human cell types.

Key Features:

• Multi-SNP Predictive Model: Uses a multi-SNP statistical model to predict gene expression levels from genotype data.
• Validation and Performance: The model was validated in Lymphoblastoid cell lines (LCL) and explained over 25% of expression variability for 232 genes.
• Cell-type Generalization: The predictive model was extended and evaluated across 14 different human cell types.
• Cell-type-specific Predictions: Produces predicted expression levels for genes across multiple cell types, enabling comparison of SNP effects in a cell-specific context.

Scientific Applications:

• Personalized genomics: Infers potential effects of individual SNP profiles on gene expression for genomic-personalization studies.
• Research on gene expression regulation: Supports investigation of regulatory mechanisms linking SNP variation to gene expression differences.
• Comparative and translational studies: Provides a framework that can inform comparative analyses and the translation of SNP-expression associations across biological contexts.

Methodology:

Integrates SNP genotype data with gene expression profiles across multiple cell types using statistical modeling and validation across independent datasets.