BACKGROUND/AIMS: We aim to quantify the effect of non-differential genotyping errors on the power of rare variant tests and identify those situations when genotyping errors are most harmful. METHODS: We simulated genotype and phenotype data for a range of sample sizes, minor allele frequencies, disease relative risks and numbers of rare variants. Genotype errors were then simulated using five different error models covering a wide range of error rates. RESULTS: Even at very low error rates, misclassifying a common homozygote as a heterozygote translates into a substantial loss of power, a result that is exacerbated even further as the minor allele frequency decreases. While the power loss from heterozygote to common homozygote errors tends to be smaller for a given error rate, in practice heterozygote to homozygote errors are more frequent and, thus, will have measurable impact on power. CONCLUSION: Error rates from genotype-calling technology for next-generation sequencing data suggest that substantial power loss may be seen when applying current rare variant tests of association to called genotypes.
BACKGROUND/AIMS: We aim to quantify the effect of non-differential genotyping errors on the power of rare variant tests and identify those situations when genotyping errors are most harmful. METHODS: We simulated genotype and phenotype data for a range of sample sizes, minor allele frequencies, disease relative risks and numbers of rare variants. Genotype errors were then simulated using five different error models covering a wide range of error rates. RESULTS: Even at very low error rates, misclassifying a common homozygote as a heterozygote translates into a substantial loss of power, a result that is exacerbated even further as the minor allele frequency decreases. While the power loss from heterozygote to common homozygote errors tends to be smaller for a given error rate, in practice heterozygote to homozygote errors are more frequent and, thus, will have measurable impact on power. CONCLUSION: Error rates from genotype-calling technology for next-generation sequencing data suggest that substantial power loss may be seen when applying current rare variant tests of association to called genotypes.
Authors: Lucy Huang; Yun Li; Andrew B Singleton; John A Hardy; Gonçalo Abecasis; Noah A Rosenberg; Paul Scheet Journal: Am J Hum Genet Date: 2009-02 Impact factor: 11.025
Authors: Lin Hou; Ning Sun; Shrikant Mane; Fred Sayward; Nallakkandi Rajeevan; Kei-Hoi Cheung; Kelly Cho; Saiju Pyarajan; Mihaela Aslan; Perry Miller; Philip D Harvey; J Michael Gaziano; John Concato; Hongyu Zhao Journal: Genet Epidemiol Date: 2016-12-26 Impact factor: 2.135
Authors: Sarah C Nelson; Kimberly F Doheny; Elizabeth W Pugh; Jane M Romm; Hua Ling; Cecelia A Laurie; Sharon R Browning; Bruce S Weir; Cathy C Laurie Journal: G3 (Bethesda) Date: 2013-10-03 Impact factor: 3.154