Identifying Maximal Perfect Haplotype Blocks
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Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-030-01722-4_3
Reference11 articles.
1. 1000 Genomes Project Consortium, Auton, A., et al.: A global reference for human geneticvariation. Nature 526(7571), 68–74 (2015)
2. Browning, S.R., Browning, B.L.: Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering. Am. J. Hum. Genet. 81(5), 1084–1097 (2007)
3. Chen, H., Hey, J., Slatkin, M.: A hidden Markov model for investigating recent positive selection through haplotype structure. Theor. Popul. Biol. 99, 18–30 (2015)
4. Chen, H., Slatkin, M.: Inferring selection intensity and allele age from multi-locus haplotype structure. G3: Genes Genomes, Genet. 3(8), 1429–1442 (2013)
5. Durbin, R.M.: Efficient haplotype matching and storage using the positional burrows-wheeler transform (PBWT). Bioinformatics 30(9), 1266–1272 (2014)
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1. Discovery of runs-of-homozygosity diplotype clusters and their associations with diseases in UK Biobank;eLife;2024-06-21
2. Multiallelic Maximal Perfect Haplotype Blocks with Wildcards via PBWT;Bioinformatics and Biomedical Engineering;2023
3. mcPBWT: Space-Efficient Multi-column PBWT Scanning Algorithm for Composite Haplotype Matching;Computational Advances in Bio and Medical Sciences;2022
4. Discovery of runs-of-homozygosity diplotype clusters and their associations with diseases in UK Biobank;2020-10-27
5. Maximal Perfect Haplotype Blocks with Wildcards;iScience;2020-06
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