TY - JOUR
T1 - The impact of data quality on the identification of complex disease genes
T2 - Experience from the Family Blood Pressure Program
AU - Chang, Yen Pei Christy
AU - Kim, James Dae Ok
AU - Schwander, Karen
AU - Rao, Dabeeru C.
AU - Miller, Mike B.
AU - Weder, Alan B.
AU - Cooper, Richard S.
AU - Schork, Nicholas J.
AU - Province, Michael A.
AU - Morrison, Alanna C.
AU - Kardia, Sharon L.R.
AU - Quertermous, Thomas
AU - Chakravarti, Aravinda
PY - 2006/4
Y1 - 2006/4
N2 - The application of genome-wide linkage scans to uncover susceptibility loci for complex diseases offers great promise for the risk assessment, treatment, and understanding of these diseases. However, for most published studies, linkage signals are typically modest and vary considerably from one study to another. The multicenter Family Blood Pressure Program has analyzed genome-wide linkage scans of over 12 000 individuals. Based on this experience, we developed a protocol for large linkage studies that reduces two sources of data error: pedigree structure and marker genotyping errors. We then used the linkage signals, before and after data cleaning, to illustrate the impact of missing and erroneous data. A comprehensive error-checking protocol is an important part of complex disease linkage studies and enhances gene mapping. The lack of significant and reproducible linkage findings across studies is, in part, due to data quality.
AB - The application of genome-wide linkage scans to uncover susceptibility loci for complex diseases offers great promise for the risk assessment, treatment, and understanding of these diseases. However, for most published studies, linkage signals are typically modest and vary considerably from one study to another. The multicenter Family Blood Pressure Program has analyzed genome-wide linkage scans of over 12 000 individuals. Based on this experience, we developed a protocol for large linkage studies that reduces two sources of data error: pedigree structure and marker genotyping errors. We then used the linkage signals, before and after data cleaning, to illustrate the impact of missing and erroneous data. A comprehensive error-checking protocol is an important part of complex disease linkage studies and enhances gene mapping. The lack of significant and reproducible linkage findings across studies is, in part, due to data quality.
KW - Data quality
KW - Family relationship
KW - Genome-wide linkage studies
UR - http://www.scopus.com/inward/record.url?scp=33646182610&partnerID=8YFLogxK
U2 - 10.1038/sj.ejhg.5201582
DO - 10.1038/sj.ejhg.5201582
M3 - Article
C2 - 16493446
AN - SCOPUS:33646182610
SN - 1018-4813
VL - 14
SP - 469
EP - 477
JO - European Journal of Human Genetics
JF - European Journal of Human Genetics
IS - 4
ER -