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1.
Hum Immunol ; 80(9): 633-643, 2019 Sep.
Article in English | MEDLINE | ID: mdl-30735756

ABSTRACT

The highly polymorphic classical human leukocyte antigen (HLA) genes display strong linkage disequilibrium (LD) that results in conserved multi-locus haplotypes. For unrelated individuals in defined populations, HLA haplotype frequencies can be estimated using the expectation-maximization (EM) method. Haplotypes can also be constructed using HLA allele segregation from nuclear families. It is straightforward to identify many HLA genotyping inconsistencies by visually reviewing HLA allele segregation in family members. It is also possible to identify potential crossover events when two or more children are available in a nuclear family. This process of visual inspection can be unwieldy, and we developed the "HaplObserve" program to standardize the process and automatically build haplotypes using family-based HLA allele segregation. HaplObserve facilitates systematically building haplotypes, and reporting potential crossover events. HLA Haplotype Validator (HLAHapV) is a program originally developed to impute chromosomal phase from genotype data using reference haplotype data. We updated and adapted HLAHapV to systematically compare observed and estimated haplotypes. We also used HLAHapV to identify haplotypes when uninformative HLA genotypes are present in families. Finally, we developed "pould", an R package that calculates haplotype frequencies, and estimates standard measures of global (locus-level) LD from both observed and estimated haplotypes.


Subject(s)
HLA Antigens/genetics , Haplotypes/genetics , Software , Alleles , Child , Gene Frequency/genetics , Genetic Loci , Heterozygote , Humans , Linkage Disequilibrium/genetics , Nuclear Family , Pedigree
2.
Biol Blood Marrow Transplant ; 24(4): 659-665, 2018 04.
Article in English | MEDLINE | ID: mdl-29288819

ABSTRACT

Informatics strategies and applications available to stem cell transplant (SCT) programs are diverse and changing rapidly. Although most hospitals have electronic medical records (EMRs), few are equipped with specialized SCT applications. Most EMRs do not contain critical elements to support SCT practice and research. Strategies to optimize information technology resources to support SCT programs are reviewed and technical and workflow support discussed. Guidance and rationale for the use of both SCT applications and EMRs are emphasized.


Subject(s)
Electronic Health Records , Medical Informatics , Stem Cell Transplantation , Animals , Humans , Medical Informatics/methods , Medical Informatics/trends
3.
Hum Immunol ; 77(3): 273-282, 2016 Mar.
Article in English | MEDLINE | ID: mdl-26546873

ABSTRACT

HLA alleles are observed in specific haplotypes, due to Linkage Disequilibrium (LD) between particular alleles. Haplotype frequencies for alleles in strong LD have been established for specific ethnic groups and racial categories. Application of high-resolution HLA typing using Next Generation Sequencing (NGS) is becoming a common practice in research and clinical laboratory settings. HLA typing errors using NGS occasionally occur due to allelic sequence imbalance or misalignment. Manual inspection of HLA genotypes is labor intensive and requires an in-depth knowledge of HLA alleles and haplotypes. We developed the "HLA Haplotype Validator (HLAHapV)" software, which inspects an HLA genotype for both the presence of common and well-documented alleles and observed haplotypes. The software also reports warnings when rare alleles, or alleles that do not belong to recognized haplotypes, are found. The software validates observable haplotypes in genotype data, providing increased confidence regarding the accuracy of the HLA typing, and thus reducing the effort involved in correcting potential HLA typing errors. The HLAHapV software is a powerful tool for quality control of HLA genotypes prior to the application of downstream analyses. We demonstrate the use of the HLAHapV software for identifying unusual haplotypes, which can lead to finding potential HLA typing errors.


Subject(s)
Computational Biology/methods , HLA Antigens/genetics , Haplotypes , Histocompatibility Testing , Software , Alleles , Databases, Genetic , Gene Frequency , High-Throughput Nucleotide Sequencing , Humans , Linkage Disequilibrium , Reproducibility of Results , Web Browser
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