Software
| HS-TDT |
You can download HS-TDT for Windows here, and HS-TDT for Unix here.
- The program HS-TDT implements the haplotype sharing TDT methods proposed by Zhang et al. (2003; Am J Hum Genet 73:566-579),
Zhang et al.(2004;Am J Hum Genet 74: 591-593), and
Sha et al. (2004) ( pdf file) to test for association using tightly linked markers for general
nuclear family data. It allows missing genotypes and aplicable both to quantitative traits and qualitative trait.
By merging the rare haplotypes, it can well control the false-positive results caused by genotyping errors (Sha et al. 2004).
- It also can estimate the haplotype frequencies based on nuclear family data.
The method implemented in this version of HS-TDT uses Partition-Ligation EM algorithm to estimate
haplotype frequencies by incorporating
nuclear family information. The program allows missing genotype, missing parents, and can deal
very large number of markers.
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| ELA |
You can download ELA for Windows here, and ELA for Linux here.
- The program ELA implements a genetic association mapping method for complex diseases
[Zhaogong Zhang, Shuanglin Zhang, Man-Yu Wong, Nicholas J. Wareham, Qiuying Sha (2007)
An Ensemble Learning Approach Jointly Modeling Main and Interaction Effects in Genetic
Association Studies. Genetic Epi. Submitted]. The method implemented in this version of
ELA uses an Ensemble Learning Approach (ELA) to jointly model main and interaction
effects in genetic association mapping. The program allows missing genotypes and
can deal with very large number of markers. The detail methods used are introduced in the above mentioned paper.
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| IPEM |
You can download IPEM for Windows here and IPEM for Linux here.
- In genome-wide association sudies, some causal variants may be completely untyped in that
only the tagging single nucleotide polymorphisms (SNPs) are genotyped. This algorithm imputes the
genotypes at untyped marker loci in a new study. It utilizes an available comprehensice
reference haplotype dataset and incorporates the inherent multi-locus linkage disequilibrium.
This software can impute the genotypes on 500,000 SNPs in 500 individuals within 32 hours.
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| Improved Score Test |
You can download R code for Improved Score Test here.
- Improved Score test is an association test proposed in the paper: Sha Q, Zhang Z, Zhang S (2011) An Improved Score Test for Genetic Association Studies. To be appeared in Genetic Epidemiology. Improved Score Test is uniformly more powerful than many commonly used association tests such as the Cochran-Armitage trend test, the allelic Chi-square test, the genotypic Chi-square test, the haplotypic Chi-square test, and the multi- marker genotypic Chi-square test among others.
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| Adaptive Weighting Test |
You can download R code for Adaptive Weighting Test here.
- Adaptive Weighting Test is an association test to test association between a phenotype and a group of variants (can be rare and common) in a genomic region by using an adaptive weighting method. The adaptive weighting test, proposed in the paper: Sha Q, Wang S, Zhang S (2011) Adaptive Clustering and Adaptive Weighting Methods to Detect Disease Associated Rare Variants, aims to test rare variant association in the presence of neutral and/or protective variants.
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| Hardy Weinberg Equilibrium Test in Structured Populations (HWES) |
You can download R code for HWES here.
- The HWES is a test to test HWE in structured populations proposed in the paper: Sha Q, Zhang S (2011) A Test of Hardy Weinberg Equilibrium in Structured Populations. To be appeared in Genetic Epidemiology. HWES can assess departure from HWE and take into account of population stratification at the same time. The HWES can distinguish departure from HWE caused by population stratification and departure from HWE caused by other factors.
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| Test the effect of the Optimally Weighted combination (TOW) of variants |
You can download R code for TOW here.
- TOW is an association test to test association between a phenotype and an optimal weighted combination of variants (can be rare and common) in a genomic region. The TOW, proposed in the paper: Sha Q, Wang X, Wang X, Zhang S (2012) Detecting Association of Rare and Common Variants by Testing an Optimally Weighted Combination of Variants (Genetic Epidemiology), aims to test association of an optimal weighted combination of rare variants.
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