RFMix-reader: Accelerated reading and processing for local ancestry studies.
bioRxiv
; 2024 Jul 18.
Article
em En
| MEDLINE
| ID: mdl-39071265
ABSTRACT
Motivation Local ancestry inference is a powerful technique in genetics, revealing population history and the genetic basis of diseases. It is particularly valuable for improving eQTL discovery and fine-mapping in admixed populations. Despite the widespread use of the RFMix software for local ancestry inference, large-scale genomic studies face challenges of high memory consumption and processing times when handling RFMix output files. Results:
Here, I present RFMix-reader, a new Python-based parsing software, designed to streamline the analysis of large-scale local ancestry datasets. This software prioritizes computational efficiency and memory optimization, leveraging GPUs when available for additional speed boosts. By overcoming these data processing hurdles, RFMix-reader empowers researchers to unlock the full potential of local ancestry data for understanding human health and health disparities.Availability:
RFMix-reader is freely available on PyPI at https//pypi.org/project/RFMix-reader/, implemented in Python 3, and supported on Linux, Windows, and Mac OS.
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MEDLINE
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article