| Title: | IGD: a simple, efficient genotype data format |
| Journal: | Bioinformatics Advances |
| Published: | 26 Dec 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40980555/ |
| DOI: | https://doi.org/10.1093/bioadv/vbaf205 |
| URL: | https://academic.oup.com/bioinformaticsadvances/advance-article-pdf/doi/10.1093/bioadv/vbaf205/64140915/vbaf205.pdf |
Publication 16441
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Abstract
Motivation: While there are a variety of file formats for storing reference-sequence-aligned genotype data, many are complex or inefficient. Programming language support for such formats is often limited. A file format that is simple to understand and implement-yet fast and small-is helpful for research on highly scalable statistical and population genetics methods.</p>
Results: We present the Indexable Genotype Data (IGD) file format, a simple uncompressed binary format that can be more than 100× faster and 3.5× smaller than vcf.gz on biobank-scale whole-genome sequence data. The implementation for reading and writing IGD in Python is under 350 lines of code, which reflects the simplicity of the format.</p>
Availability and implementation: A C++ library for reading and writing IGD, and tooling to convert .vcf.gz files, can be found at https://github.com/aprilweilab/picovcf. A Python library is at https://github.com/aprilweilab/pyigd.</p>
2 Authors
- Drew DeHaas
- Xinzhu Wei
1 Application
| Application ID | Title |
|---|---|
| 97908 | Scalable and accurate methods for understanding human complex traits |
Enabling scientific discoveries that improve human health