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Uniform processing and analysis of IGVF massively parallel reporter assay data with MPRAsnakeflow
Jonathan D Rosen1, Arjun Devadas Vasanthakumari2, Kilian Salomon3
1Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599-7264, USA.
Genome Research
|August 11, 2026
Summary
Standardizing massively parallel reporter assays (MPRAs) is crucial for understanding genomic variation. New tools and formats ensure reproducible analysis of MPRA data, advancing regulatory genomics research.
Area of Science:
- Genomics
- Regulatory Genomics
- Computational Biology
Background:
- Identifying human genomic alterations linked to traits and disorders is challenging, especially for noncoding variations lacking functional annotation.
- Experimental evidence is vital for interpreting genetic alteration effects, with Massively Parallel Reporter Assays (MPRAs) offering a high-throughput solution.
- Current MPRA data suffers from a lack of standardization, hindering integration, reproducibility, and meta-analyses.
Purpose of the Study:
- To address challenges in MPRA data integration and reproducibility by developing community standards and analysis pipelines.
- To present harmonized file formats and computational tools (MPRAlib and MPRAsnakeflow) for uniform MPRA data processing.
- To establish best practices for MPRA data generation and analysis through investigation of technical variability.
Main Methods:
- The Impact of Genomic Variation on Function (IGVF) Consortium established an MPRA focus group to develop standards.
- Development of MPRAlib and MPRAsnakeflow for processing MPRA data from raw reads to visualization.
- Investigation of technical variability sources, including barcode bias and delivery methods, using diverse MPRA datasets.
Main Results:
- Community standards, harmonized file formats, and robust analysis pipelines for MPRAs have been developed.
- MPRAlib and MPRAsnakeflow enable uniform processing and visualization of MPRA data.
- Identification of technical variability sources and establishment of best practices for MPRA data generation and analysis.
Conclusions:
- The developed standards and tools facilitate robust, reproducible MPRA research and large-scale data integration.
- Publicly available tools and standards provide a foundation for collaborative efforts in regulatory genomics.
- Standardization of MPRA analysis is essential for advancing the understanding of genomic variation's impact on function.
