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Related Experiment Video

Updated: Jan 27, 2026

Functional Assessment of BRCA1 variants using CRISPR-Mediated Base Editors

Functional Assessment of BRCA1 variants using CRISPR-Mediated Base Editors

Published on: February 28, 2021

GenomeWarp: an alignment-based variant coordinate transformation.

Cory Y McLean^1,2, Yeongwoo Hwang^1,3, Ryan Poplin^1,2

¹Verily Life Sciences, Mountain View, CA, USA.

Bioinformatics (Oxford, England)

|March 28, 2019

Summary

This summary is machine-generated.

GenomeWarp efficiently transforms genome assembly data, including short variants, between reference genomes. This tool minimizes errors, ensuring accurate data analysis across different genome builds.

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Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Reference genomes are regularly updated with error corrections and improvements.
Analyzing data across different genome assemblies requires coordinate transformation.
Existing tools lack support for accurate genome-wide short variation transformation.

Purpose of the Study:

To present GenomeWarp, a novel tool for transforming variants between genome assemblies.
To enable efficient and accurate conversion of genome-wide short variation data.

Main Methods:

GenomeWarp is a Java-based tool designed for efficient variant transformation.
It employs a conservative transformation approach to minimize false positives/negatives.
The tool handles both regions and short variants across genome assemblies.

Main Results:

GenomeWarp successfully transforms regions and short variants between genome assemblies.
Over 99% of regions and short variants were converted from a representative human genome.
The transformation process minimizes false positive and negative variants in the target genome.

Conclusions:

GenomeWarp provides an efficient and accurate solution for transforming genome-wide short variation data.
This tool facilitates the integration of data analyzed on older reference genomes with newer assemblies.
GenomeWarp ensures data integrity and accuracy when working with evolving genomic references.