Literature DB >> 23702557

HapBoost: a fast approach to boosting haplotype association analyses in genome-wide association studies.

Xiang Wan1, Can Yang, Qiang Yang, Hongyu Zhao, Weichuan Yu.   

Abstract

Genome-wide association study (GWAS) has been successful in identifying genetic variants that are associated with complex human diseases. In GWAS, multilocus association analyses through linkage disequilibrium (LD), named haplotype-based analyses, may have greater power than single-locus analyses for detecting disease susceptibility loci. However, the large number of SNPs genotyped in GWAS poses great computational challenges in the detection of haplotype associations. We present a fast method named HapBoost for finding haplotype associations, which can be applied to quickly screen the whole genome. The effectiveness of HapBoost is demonstrated by using both synthetic and real data sets. The experimental results show that the proposed approach can achieve comparably accurate results while it performs much faster than existing methods.

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Year:  2013        PMID: 23702557     DOI: 10.1109/TCBB.2013.6

Source DB:  PubMed          Journal:  IEEE/ACM Trans Comput Biol Bioinform        ISSN: 1545-5963            Impact factor:   3.710


  2 in total

1.  Regionally Smoothed Meta-Analysis Methods for GWAS Datasets.

Authors:  Ferdouse Begum; Monir H Sharker; Stephanie L Sherman; George C Tseng; Eleanor Feingold
Journal:  Genet Epidemiol       Date:  2015-12-28       Impact factor: 2.135

2.  A method combining a random forest-based technique with the modeling of linkage disequilibrium through latent variables, to run multilocus genome-wide association studies.

Authors:  Christine Sinoquet
Journal:  BMC Bioinformatics       Date:  2018-03-27       Impact factor: 3.169

  2 in total

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