Abstract
Multimarker Transmission/Disequilibrium Tests (TDTs) are very robust association tests to population admixture and structure which may be used to identify susceptibility loci in genome-wide association studies. Multimarker TDTs using several markers may increase power by capturing high-degree associations. However, there is also a risk of spurious associations and power reduction due to the increase in degrees of freedom. In this study we show that associations found by tests built on simple null hypotheses are highly reproducible in a second independent data set regardless the number of markers. As a test exhibiting this feature to its maximum, we introduce the multimarker -Groups TDT ( ), a test which under the hypothesis of no linkage, asymptotically follows a distribution with degree of freedom regardless the number of markers. The statistic requires the division of parental haplotypes into two groups: disease susceptibility and disease protective haplotype groups. We assessed the test behavior by performing an extensive simulation study as well as a real-data study using several data sets of two complex diseases. We show that test is highly efficient and it achieves the highest power among all the tests used, even when the null hypothesis is tested in a second independent data set. Therefore, turns out to be a very promising multimarker TDT to perform genome-wide searches for disease susceptibility loci that may be used as a preprocessing step in the construction of more accurate genetic models to predict individual susceptibility to complex diseases.
Highlights
Current commercially-available genotyping technologies for identifying Single-Nucleotide Polymorphisms (SNPs) are able to scan a few hundred thousands of these binary markers in a single chip array
In-silico genome-wide single nucleotide polymorphisms (SNP) filtering can be performed as a preprocessing step, before more expensive, molecular-based experimentation, as a way to reduce costs when searching for loci that may be associated to a disease
Transmission/Disequilibrium Tests (TDTs) is enhanced by multimarker TDTs when there are no sequenced markers that belong to the disease susceptibility locus, but which are in strong linkage disequilibrium (LD) with it [5,6]
Summary
Current commercially-available genotyping technologies for identifying Single-Nucleotide Polymorphisms (SNPs) are able to scan a few hundred thousands of these binary markers in a single chip array With such arrays, in-silico genome-wide single nucleotide polymorphisms (SNP) filtering can be performed as a preprocessing step, before more expensive, molecular-based experimentation, as a way to reduce costs when searching for loci that may be associated to a disease. Different multimarker generalizations of TDT, such as mTDT [3,4], enhance the test by detecting marker interaction, i.e., when a single marker is independent of the trait, but there is association when more than one marker are considered together This conditional dependence may point out to gene-gene interactions (epistasis), or just to a disease susceptibility gene whose disease allele needs more than one marker to be tagged. TDT is enhanced by multimarker TDTs when there are no sequenced markers that belong to the disease susceptibility locus, but which are in strong linkage disequilibrium (LD) with it [5,6]
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