ArticlePloS one2015
Using Hamming Distance as Information for SNP-Sets Clustering and Testing in Disease Association Studies.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- A latent genetic subtype of major depression identified by whole-exome genotyping data in a Mexican-American cohort.Translational psychiatry · 2017Trial
- Machine Learning-Based Accurate Full-Sib Family Assignment in Sturgeon Using Whole-Genome Sequencing Data.International journal of molecular sciences · 2026Article
- Immune-deficient bacteria serve as gateways to genetic exchange and microbial evolution.Nature communications · 2026Article
- Genomic insights intoFrontiers in plant science · 2026Article
- Accurate structure-activity relationship prediction of antioxidant peptides using a multimodal deep learning framework.Journal of cheminformatics · 2025Article
- Molecular Footprints of Quaternary Climate Fluctuations in the Circumpolar Tundra Shrub Dwarf Birch.Molecular ecology · 2025Article
- Effects of landscape, resource use, and body size on genetic structure in bee populations.Ecology and evolution · 2024Article
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- Novel Network Method Major Minor Variation Clustering Enables Identification of Poliovirus Clusters with High-Resolution Linkages.Journal of computational biology : a journal of computational molecular cell biology · 2023Article
- Simulations of rate of genetic gain in dry bean breeding programs.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023Article
- Postsynaptic density radiation signature following space irradiation.Frontiers in physiology · 2023Article
- A machine learning-based SNP-set analysis approach for identifying disease-associated susceptibility loci.Scientific reports · 2022Article
- A Panel of rSNPs Demonstrating Allelic Asymmetry in Both ChIP-seq and RNA-seq Data and the Search for Their Phenotypic Outcomes through Analysis of DEGs.International journal of molecular sciences · 2021Article
- Adaptive divergence, neutral panmixia, and algal symbiont population structure in the temperate coralPeerJ · 2020Article
- SNP variable selection by generalized graph domination.PloS one · 2019Article
- Reexamining Dis/Similarity-Based Tests for Rare-Variant Association with Case-Control Samples.Genetics · 2018Article
- Unlocking the diversity of genebanks: whole-genome marker analysis of Swiss bread wheat and spelt.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2018Article
- Utility of Genetic Testing in Addition to Mammography for Determining Risk of Breast Cancer Depends on Patient Age.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2018Article
- AveDissR: An R function for assessing genetic distinctness and genetic redundancy.Applications in plant sciences · 2017Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The availability of high-throughput genomic data has led to several challenges in recent genetic association studies, including the large number of genetic variants that must be considered and the computational complexity in statistical analyses. Tackling these problems with a marker-set study such as SNP-set analysis can be an efficient solution. To construct SNP-sets, we first propose a clustering algorithm, which employs Hamming distance to measure the similarity between strings of SNP genotypes and evaluates whether the given SNPs or SNP-sets should be clustered. A dendrogram can then be constructed based on such distance measure, and the number of clusters can be determined. With the resulting SNP-sets, we next develop an association test HDAT to examine susceptibility to the disease of interest. This proposed test assesses, based on Hamming distance, whether the similarity between a diseased and a normal individual differs from the similarity between two individuals of the same disease status. In our proposed methodology, only genotype information is needed. No inference of haplotypes is required, and SNPs under consideration do not need to locate in nearby regions. The proposed clustering algorithm and association test are illustrated with applications and simulation studies. As compared with other existing methods, the clustering algorithm is faster and better at identifying sets containing SNPs exerting a similar effect. In addition, the simulation studies demonstrated that the proposed test works well for SNP-sets containing a large proportion of neutral SNPs. Furthermore, employing the clustering algorithm before testing a large set of data improves the knowledge in confining the genetic regions for susceptible genetic markers.
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