GWASTools

GWASTools provides R/Bioconductor-based functions for quality control, NetCDF-based storage, and analysis of genome-wide association study (GWAS) data to identify associations between genetic variants and traits.

Key Features:

• NetCDF storage: Stores GWAS datasets in NetCDF format to enable efficient handling of datasets that exceed R memory limits.
• R/Bioconductor integration: Operates within R/Bioconductor and leverages R statistical libraries for analysis.
• Data format conversion: Imports and converts data from multiple formats, including formats derived from sequencing variants.
• Genotype–intensity linkage: Links genotypes and intensity data with corresponding sample and SNP annotations.
• Quality control: Implements quality control checks for sample quality and genotype quality.
• Statistical association analysis: Performs statistical analyses to detect associations between genetic variants, including SNPs, and phenotypic traits.
• Data cleaning and downstream analysis: Provides tools for data cleaning and subsequent analysis to support reproducibility of GWAS findings.

Scientific Applications:

• GWAS quality control: Conducts sample- and genotype-level quality control to ensure integrity of GWAS datasets.
• Association discovery: Identifies associations between SNPs/genetic variants and traits or diseases.
• Large-scale genotype and intensity analysis: Enables analysis of large-scale genotype and intensity datasets that exceed typical in-memory capacities.
• Integration of sequencing-derived variants: Supports use of data originating from sequencing variant calls in GWAS analyses.

Methodology:

Stores datasets in NetCDF; imports and converts multiple input formats including sequencing-variant-derived formats; links genotypes and intensity data with sample and SNP annotations; implements sample and genotype quality-control checks; and performs statistical analyses to identify associations between genetic variants and traits.