SAQC: SNP array quality control

Background: Genome-wide single-nucleotide polymorphism (SNP) arrays containing hundreds of thousands of SNPs from the human genome have proven useful for studying important human genome questions. Data quality of SNP arrays plays a key role in the accuracy and precision of downstream data analyses. However, good indices for assessing data quality of SNP arrays have not yet been developed. Results: We developed new quality indices to measure the quality of SNP arrays and/or DNA samples and investigated their statistical properties. The indices quantify a departure of estimated individual-level allele frequencies (AFs) from expected frequencies via standardized distances. The proposed quality indices followed lognormal distributions in several large genomic studies that we empirically evaluated. AF reference data and quality index reference data for different SNP array platforms were established based on samples from various reference populations. Furthermore, a confidence interval meth...

• Type: Journal
• Year: 2011
• Where: BMCBI
• Authors: Hsin-Chou Yang, Hsin-Chi Lin, Meijyh Kang, Chun-Houh Chen, Chien-Wei Lin, Ling-Hui Li, Jer-Yuarn Wu, Yuan-Tsong Chen, Wen-Harn Pan
• Keywords: Artificial Intelligence, BMCBI 2011, Dna Samples, Quality Indices, Snp Arrays