OpenVariant: a toolkit to parse and operate multiple input file formats.

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• High-throughput DNA sequencing enables identification of genetic variants in tumors.
• Inconsistencies in variant annotation tools and databases hinder cancer genomic analyses.
• Standardization of variant data remains a challenge in the field.

Purpose of the Study:

• To present OpenVariant, a Python package for processing diverse genetic variant data.
• To facilitate seamless reading, parsing, and refinement of variant files.
• To improve the integration of variant data in cancer genomic analyses.

Main Methods:

• Development of an easily extendable Python package named OpenVariant.
• Implementation of functions for reading and parsing various input file formats.
• Inclusion of customizable structures for variant data refinement within a single process.

Main Results:

• OpenVariant provides a unified approach to handle diverse genetic variant data.
• The package streamlines the process of variant data preparation for analysis.
• It aims to reduce variability issues encountered in cancer genomic research.

Conclusions:

• OpenVariant offers a practical solution for managing and integrating genetic variant data.
• The package enhances the efficiency and reliability of cancer genomic analyses.
• It promotes better utilization of genetic variant information in research and clinical settings.