CLUSTAG: hierarchical clustering and graph methods for selecting tag SNPs

Ao, Sio-Iong; Yip, Kevin Y.; Ng, Michael K.; Cheung, David W.; Fong, Pui-Yee; Melhado, Ian G.; Sham, Pak C.

doi:10.1093/bioinformatics/bti201

Cited by 76 publications

(32 citation statements)

References 5 publications

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“…8 More recently investigation of genetic variation in DAT1 in English and Taiwanese samples suggested that the association is specific to a haplotype of the 10-repeat allele, with the 3-repeat allele of a second VNTR located within intron 8. 31 Analysis of these two markers in this sample revealed the same pattern, with only the 10-3 haplotype showing over transmission from heterozygote parents to their affected offspring (haplotype 34 and rs6347. 38,39 We detected a trend with over transmission of the same allele (A-allele) in rs6347 and no association with rs27072.…”

Section: Dat1mentioning

confidence: 59%

“…We used the 'CompleteLink routine' within CLUSTAG that implements a hierarchical clustering algorithm (http://hkumath.hku.hk/web/link/CLUS-TAG/CLUSTAG.html. 34 Hierarchical clustering starts with a square matrix of pair-wise distances (as defined by 1-R 2 ) between the SNPs to be clustered. The rationale is that the noncentrality parameter (NCP) for a tSNP is the product of the NCP at the causal SNP and the R 2 .…”

Section: Clinical Proceduresmentioning

confidence: 99%

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The analysis of 51 genes in DSM-IV combined type attention deficit hyperactivity disorder: association signals in DRD4, DAT1 and 16 other genes

et al. 2006

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Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder, starting in early childhood and persisting into adulthood in the majority of cases. Family and twin studies have demonstrated the importance of genetic factors and candidate gene association studies have identified several loci that exert small but significant effects on ADHD. To provide further clarification of reported associations and identify novel associated genes, we examined 1038 single-nucleotide polymorphisms (SNPs) spanning 51 candidate genes involved in the regulation of neurotransmitter pathways, particularly dopamine, norepinephrine and serotonin pathways, in addition to circadian rhythm genes. Analysis used within family tests of association in a sample of 776 DSM-IV ADHD combined type cases ascertained for the International Multi-centre ADHD Gene project. We found nominal significance with one or more SNPs in 18 genes, including the two most replicated findings in the literature: DRD4 and DAT1. Gene-wide tests, adjusted for the number of SNPs analysed in each gene, identified associations with TPH2, ARRB2, SYP, DAT1, ADRB2, HES1, MAOA and PNMT. Further studies will be needed to confirm or refute the observed associations and their generalisability to other samples. Molecular Psychiatry (2006) 11, 934-953.

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Section: Dat1mentioning

confidence: 59%

Section: Clinical Proceduresmentioning

confidence: 99%

The analysis of 51 genes in DSM-IV combined type attention deficit hyperactivity disorder: association signals in DRD4, DAT1 and 16 other genes

et al. 2006

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“…Tagging SNPs were selected using two methods. We used the ''CompleteLink routine'' within CLUSTAG that implements a hierarchical clustering algorithm (hkumath.hku.hk/web/link/ CLUSTAG/CLUSTAG.html) [Ao et al, 2005]. The second method used the default algorithm in Haploview (www.broad.mit.edu/mpg/haploview) from Gabriel et al [2002].…”

Section: Methodsmentioning

confidence: 99%

Population differences in the International Multi‐Centre ADHD Gene Project

Neale

Sham

Purcell

et al. 2007

Genetic Epidemiology

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) ascertained from clinics for combined-type attention definity hyperactivity disorder in an offspring. 863 SNPs were successfully genotyped across 47 autosomal genes implicated in psychiatric disorders yielding a single nucleotide polymorphism (SNP) density of approximately one SNP per 2.5 kb. A global test of heterogeneity showed 269 SNPs nominally significant (expected 43). Inclusion of the Israeli population accounted for approximately 70% of these nominally significant tests. Hardy-Weinberg equilibrium tests suggest that combining all these populations would induce stratification, but that the Northern European populations (Belgium, England, Germany, Holland, and Ireland) could be appropriate. Tag SNPs were generated using pair-wise and aggressive tagging from Carlson et al. [2004] and de Bakker et al. [2005], respectively, in each population and applied to the other populations. Cross-population performance across Northern Europe was consistent with within population comparisons. Smaller sample size for each population tended to yield more problems for the generation of aggressive tags and the application of pair-wise tags. Any case-control sample employing an Israeli sample with Northern Europeans must consider stratification. A Northern European tag set, however, appears to be appropriate for capturing the variation across populations. Genet. Epidemiol. 32:98-107, 2008. r 2007 Wiley-Liss, Inc.

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“…Enhanced Correlation search technique [29] has been applied for clustering gene expression data. CLUSTAG [3], hierarchical clustering and graph based method has been applied for selecting tag SNPs.…”

Section: Introductionmentioning

confidence: 99%

Enhanced Hierarchical Clustering for Gene Expression data

Geetha¹,

Arock²

2010

IJCA

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Micro arrays are used to assess the transcriptome of many biological systems that has generated an enormous amount of data. Cluster analysis is a technique used to group and analyze micro array data. Identification of groups of genes that manifest similar expression patterns is a key step in the analysis of gene expression data. Hierarchical clustering is the one of the clustering techniques used for this purpose. In this paper, we design an enhanced hierarchical clustering algorithm which scans the dataset and calculates distance matrix only once unlike other papers, (up to authors' knowledge). Our main contribution is to reduce time, even when a large database is analyzed. Also, the results of hierarchical clustering are represented as a binary tree which gives clarity in grouping and further helps to find clustered objects easily. Our algorithm is able to retrieve number of clusters with the help of cut distance and measures the quality with validation index in order to obtain the best one; does not require initial parameter like number of clusters.

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CLUSTAG: hierarchical clustering and graph methods for selecting tag SNPs

Abstract: mng@maths.hku.hk.

Cited by 76 publications

References 5 publications

The analysis of 51 genes in DSM-IV combined type attention deficit hyperactivity disorder: association signals in DRD4, DAT1 and 16 other genes

The analysis of 51 genes in DSM-IV combined type attention deficit hyperactivity disorder: association signals in DRD4, DAT1 and 16 other genes

Population differences in the International Multi‐Centre ADHD Gene Project

Enhanced Hierarchical Clustering for Gene Expression data

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