rfmix-reader

rfmix-reader streamlines the analysis of large-scale local ancestry datasets by efficiently reading and processing output files from RFMix, a software that estimates local ancestry in admixed populations.

Key Features:

• Memory Optimization: Employs lazy loading to minimize memory consumption when handling RFMix output files.
• GPU Acceleration: Leverages GPUs when available for additional speed boosts in processing.
• Computational Efficiency: Prioritizes computational efficiency to overcome high memory consumption and processing times in large-scale genomic studies.

Scientific Applications:

• Population History Research: Enables analysis of local ancestry data to reveal population history.
• Disease Genetics: Supports investigation of the genetic basis of diseases through local ancestry inference.
• eQTL Discovery: Improves eQTL discovery in admixed populations via efficient processing of local ancestry data.
• Fine-Mapping: Facilitates fine-mapping in admixed populations by streamlining local ancestry dataset analysis.
• Health Disparities Research: Empowers researchers to use local ancestry data for understanding human health and health disparities.

Methodology:

rfmix-reader is implemented in Python 3 and uses lazy loading to minimize memory consumption, with optional GPU acceleration for additional speed.