MPRAscore

MPRAscore performs robust, non-parametric analysis of massively parallel reporter assay (MPRA) data to infer allele-specific transcriptional effects and estimate variant effect sizes.

Key Features:

• Allele-Specific Effect Inference: Infers allele-specific effects on transcription from MPRA datasets.
• Weighted, Variance-Regularized Methodology: Employs a weighted, variance-regularized approach to calculate variant effect sizes robustly.
• Non-Parametric Significance Testing: Utilizes permutation-based testing to assess statistical significance without assuming normality or independence.

Scientific Applications:

• Functional Genomics: Quantifies how specific DNA sequence variants affect transcriptional activity across tested sequences.
• Disease Research: Identifies variants that alter transcriptional activity and may contribute to disease mechanisms.
• Regulatory Element Analysis: Evaluates the transcriptional impact of non-coding regulatory elements and sequence perturbations.

Methodology:

Weighted variance regularization for effect size calculation; permutation-based non-parametric significance testing; and inference of allele-specific effects from MPRA measurements.