HTRX: an R package for learning non-contiguous haplotypes associated with a phenotype
Author:
Affiliation:
1. Department of Statistical Science, School of Mathematics, University of Bristol , Bristol BS8 1UG, UK
2. Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol , Bristol BS8 2BN, UK
Abstract
Funder
China Scholarship Council
Publisher
Oxford University Press (OUP)
Subject
Computer Science Applications,Genetics,Molecular Biology,Structural Biology
Link
https://academic.oup.com/bioinformaticsadvances/advance-article-pdf/doi/10.1093/bioadv/vbad038/49603819/vbad038.pdf
Reference13 articles.
1. A new look at the statistical model identification;Akaike;IEEE Trans. Automat. Contr,1974
2. Powerful testing via hierarchical linkage disequilibrium in haplotype association studies;Balliu;Biom. J,2019
3. The NHGRI-EBI GWAS catalog of published genome-wide association studies, targeted arrays and summary statistics 2019;Buniello;Nucleic Acids Res,2019
4. Bayesian variable selection regression for genome-wide association studies and other large-scale problems;Guan;Ann. Appl. Stat,2011
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1. Elevated genetic risk for multiple sclerosis emerged in steppe pastoralist populations;Nature;2024-01-10
2. HTRX: Haplotype Trend Regression with eXtra Flexibility (HTRX);CRAN: Contributed Packages;2022-10-11
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