title: SNPQC--an R pipeline for quality control of Illumina SNP genotyping array data.
abstract: In genome-wide association studies, quality control (QC) of genotypes is important to avoid spurious results. It is also important to maintain long-term data integrity, particularly in settings with ongoing genotyping (e.g. estimation of genomic breeding values). Here we discuss SNPQc, a fully automated pipeline to perform QC analyses of Illumina SNP array data. It applies a wide range of common quality metrics with user-defined filtering thresholds to generate a comprehensive QC report and a filtered dataset, including a genomic relationship matrix, ready for further downstream analyses which make it amenable for integration in high-throughput environments. SNPQC also builds a database to store genotypic, phenotypic and quality metrics to ensure data integrity and the option of integrating more samples from subsequent runs. The program is generic across species and array designs, providing a convenient interface between the genotyping laboratory and downstream genome-wide association study or genomic prediction.
authors.affiliation: The Centre for Genetic Analyses and Applications, University of New England, Armidale, NSW, Australia.
authors.forename: Cedric
authors.initials: C
authors.lastname: Gondro
authors.forename: Laercio R
authors.initials: LR
authors.lastname: Porto-Neto
authors.forename: Seung Hwan
authors.initials: SH
authors.lastname: Lee
mesh_terms: D030541:Databases, Genetic; D001330:Electronic Data Processing / Q000379:methods*; D005838:Genotype; D060005:Genotyping Techniques / Q000379:methods; D020411:Oligonucleotide Array Sequence Analysis; D020641:Polymorphism, Single Nucleotide; D011786:Quality Control; D012984:Software
keywords: chip; genome-wide association studies; genomic selection; single nucleotide polymorphism