ArticleBMC proceedings2009
Data modeling as a main source of discrepancies in single and multiple marker association methods.
Article in BMC proceedings, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Impact of prior specifications in a shrinkage-inducing Bayesian model for quantitative trait mapping and genomic prediction.Genetics, selection, evolution : GSE · 2013Article
- Comparison of analyses of the QTLMAS XII common dataset. II: genome-wide association and fine mapping.BMC proceedings · 2009Article
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Authors and funding
3 authors.
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Abstract
backgroundGenome-wide association studies have successfully identified several loci underlying complex diseases in humans. The development of high density SNP maps in domestic animal species should allow the detection of QTLs for economically important traits through association studies with much higher accuracy than traditional linkage analysis. Here we report the association analysis of the dataset simulated for the XII QTL-MAS meeting (Uppsala). We used two strategies, single marker association and haplotype-based association (Blossoc) that were applied to i) the raw data, and ii) the data corrected for infinitesimal, sex and generation effects.
resultsBoth methods performed similarly in detecting the most strongly associated SNPs, about ten loci in total. The most significant ones were located in chromosomes 1, 4 and 5. Overall, the largest differences were found between corrected and raw data, rather than between single and multiple marker analysis. The use of raw data increased greatly the number of significant loci, but possibly also the rate of false positives. Bootstrap model aggregation removed most of discrepancies between adjusted and raw data when SMA was employed.
conclusionModel choice should be carefully considered in genome-wide association studies.
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