Spoiling the whole bunch: quality control aimed at preserving the integrity of high-throughput genotyping.

Abstract:

:False-positive or false-negative results attributable to undetected genotyping errors and confounding factors present a constant challenge for genome-wide association studies (GWAS) given the low signals associated with complex phenotypes and the noise associated with high-throughput genotyping. In the context of the genetics of kidneys in diabetes (GoKinD) study, we identify a source of error in genotype calling and demonstrate that a standard battery of quality-control (QC) measures is not sufficient to detect and/or correct it. We show that, if genotyping and calling are done by plate (batch), even a few DNA samples of marginally acceptable quality can profoundly alter the allele calls for other samples on the plate. In turn, this leads to significant differential bias in estimates of allele frequency between plates and, potentially, to false-positive associations, particularly when case and control samples are not sufficiently randomized to plates. This problem may become widespread as investigators tap into existing public databases for GWAS control samples. We describe how to detect and correct this bias by utilizing additional sources of information, including raw signal-intensity data.

journal_name

Am J Hum Genet

authors

Pluzhnikov A,Below JE,Konkashbaev A,Tikhomirov A,Kistner-Griffin E,Roe CA,Nicolae DL,Cox NJ

doi

10.1016/j.ajhg.2010.06.005

subject

Has Abstract

pub_date

2010-07-09 00:00:00

pages

123-8

issue

1

eissn

0002-9297

issn

1537-6605

pii

S0002-9297(10)00308-3

journal_volume

87

pub_type

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