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satmut_utils: a simulation and variant calling package for multiplexed assays of variant effect
Ian Hoskins1, Song Sun2,3, Atina Cote2,3
1Department of Molecular Biosciences, University of Texas at Austin, Austin, TX, 78712, USA.
Genome Biology
|April 20, 2023
Summary
Millions of genetic variants
Area of Science:
- Genomics
- Molecular Biology
- Bioinformatics
Background:
- The effects of numerous genetic variants on molecular phenotypes are largely unknown.
- Existing Multiplexed Assays of Variant Effect (MAVE) software lacks standardization and scalability for large genetic targets.
Purpose of the Study:
- To introduce satmut_utils, a software package for MAVE simulation and variant quantification.
- To benchmark existing MAVE software and introduce a new method for analyzing variant effects on mRNA abundance.
Main Methods:
- Developed satmut_utils for high-performance MAVE data analysis.
- Benchmarked MAVE software using simulated and real-world MAVE data.
- Quantified mRNA abundance for thousands of cystathionine beta-synthase variants using experimental methods.
Main Results:
- satmut_utils provides a flexible and scalable solution for MAVE analysis.
- The study identified thousands of cystathionine beta-synthase variants affecting mRNA abundance.
- Demonstrated that genetic variants can significantly alter mRNA abundance.
Conclusions:
- satmut_utils enhances the analysis of Multiplexed Assays of Variant Effect.
- Genetic variants have a substantial impact on mRNA abundance, influencing molecular phenotypes.
- This work provides a foundation for understanding the functional impact of genetic variation.
