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Pacybara: Accurate long-read sequencing for barcoded mutagenized allelic libraries
Jochen Weile1,2,3,4, Gabrielle Ferra5, Gabriel Boyle5
1Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, M5G 1X5, Canada.
Biorxiv : the Preprint Server for Biology
|March 3, 2023
Summary
Pacybara software addresses long-read sequencing errors in mutagenized libraries for multiplexed assays of variant effects (MAVEs). It accurately clusters barcoded reads, resolves non-unique barcodes, and identifies chimeric clones for improved genotype-phenotype mapping.
Area of Science:
- Genomics
- Bioinformatics
- Molecular Biology
Background:
- Long-read sequencing offers advantages but struggles with high error rates.
- Barcodes are crucial for linking genotypes to phenotypes in mutagenized libraries, especially for multiplexed assays of variant effects (MAVEs).
- Existing sequencing pipelines fail to adequately handle sequencing errors and non-unique barcodes, hindering accurate genotype-phenotype association.
Conclusions:
- Pacybara provides a robust solution for analyzing long-read sequencing data from barcoded mutagenized libraries.
- The software enhances the reliability of genotype-phenotype mapping in MAVEs by mitigating sequencing errors and barcode ambiguity.
- Pacybara facilitates more accurate clinical variant interpretation through improved MAVE data analysis.
