MPRA design tools

MPRA design tools facilitates design and optimization of massively parallel reporter assays by performing power analysis, simulating experimental parameters, and automating generation of synthetic barcoded construct sequences from Variant Call Format (VCF) inputs to enable functional assessment of genetic variants.


Key Features:

  • Power analysis: Calculates statistical power to optimize assay parameters and predict sensitivity for detecting true effects.
  • Construct design automation: Parses Variant Call Format (VCF) files and automatically generates sequences for synthetic barcoded constructs for MPRA libraries.
  • Parameter simulation: Simulates changes to experimental parameters to predict their impact on assay power and outcomes.
  • Data-driven calibration: Calibrates recommendations and output metrics using empirical data from prior MPRA studies.

Scientific Applications:

  • Functional annotation of non-coding variants: Assess effects of non-coding DNA variants on gene expression via reporter activity.
  • Gene regulation studies: Analyze transcriptional activity across multiple constructs to investigate regulatory element function and networks.
  • Personalized medicine research: Characterize variant-specific effects on expression to inform variant interpretation and therapeutic strategies.

Methodology:

Computational methods explicitly include statistical power analysis, automated sequence generation of synthetic barcoded constructs from VCF input, simulation of experimental parameter changes to predict assay power, calibration using empirical MPRA datasets, and implementation of these computations in an R package.

Topics

Details

Tool Type:
library, web application
Operating Systems:
Linux, Windows, Mac
Programming Languages:
R
Added:
6/3/2018
Last Updated:
11/25/2024

Operations

Publications

Ghazi AR, Chen ES, Henke DM, Madan N, Edelstein LC, Shaw CA. Design tools for MPRA experiments. Bioinformatics. 2018;34(15):2682-2683. doi:10.1093/bioinformatics/bty150. PMID:30052913. PMCID:PMC6454564.

PMID: 30052913
PMCID: PMC6454564
Funding: - United States National Institutes of Health: R01HL128234

Documentation