Human leukocyte antigen (HLA) A-C-B-DRB1-DQB1 haplotype segregation analysis among 2152 families in China and the comparison to expectation-maximization algorithm result

According to doctors’ typing applications and laboratory standard operation procedure, sequence-based typing plus sequence-specific oligonucleotide probe methods were performed for high-resolution HLA-A, B, C, DRB1, and DQB1 typing for all patients. [...]the patients’ typing results were used as pha...

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Published in:Chinese medical journal Vol. 134; no. 14; pp. 1741 - 1743
Main Authors: Li, Yang, Chen, Lu-Yao, Zhang, Teng-Teng, Yuan, Xiao-Ni, Bao, Xiao-Jing, He, Jun
Format: Journal Article
Language:English
Published: China Lippincott Williams & Wilkins 26.03.2021
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ISSN:0366-6999, 2542-5641, 2542-5641
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Abstract According to doctors’ typing applications and laboratory standard operation procedure, sequence-based typing plus sequence-specific oligonucleotide probe methods were performed for high-resolution HLA-A, B, C, DRB1, and DQB1 typing for all patients. [...]the patients’ typing results were used as phase-known and phase-unknown data to obtain observed and expected HFs, respectively, by the direct counting EM algorithm (only HFs >1 × 10–5 were outputted by Arlequin). The P values of the Chi-square test showed that there were no statistically significant differences between observed and expected haplotypes, not only in total overlapping data (P = 0.2424) and common data (HF ≥ 0.1%, P = 0.3698) but also in less-common data (HF < 0.1%, P = 0.1582). [...]the tendencies of observed and expected haplotypes are coincident, and the tendency concordance of common data is the best; then, the total overlapping data last the less common data. [...]EM could miss less-common real haplotypes but built incorrectly less-common haplotypes. [...]identifying less common haplotypes from segregation analysis must be used for checking and as supplements to cover the shortage of EM.
AbstractList According to doctors’ typing applications and laboratory standard operation procedure, sequence-based typing plus sequence-specific oligonucleotide probe methods were performed for high-resolution HLA-A, B, C, DRB1, and DQB1 typing for all patients. [...]the patients’ typing results were used as phase-known and phase-unknown data to obtain observed and expected HFs, respectively, by the direct counting EM algorithm (only HFs >1 × 10–5 were outputted by Arlequin). The P values of the Chi-square test showed that there were no statistically significant differences between observed and expected haplotypes, not only in total overlapping data (P = 0.2424) and common data (HF ≥ 0.1%, P = 0.3698) but also in less-common data (HF < 0.1%, P = 0.1582). [...]the tendencies of observed and expected haplotypes are coincident, and the tendency concordance of common data is the best; then, the total overlapping data last the less common data. [...]EM could miss less-common real haplotypes but built incorrectly less-common haplotypes. [...]identifying less common haplotypes from segregation analysis must be used for checking and as supplements to cover the shortage of EM.
Author Zhang, Teng-Teng
Li, Yang
Yuan, Xiao-Ni
Bao, Xiao-Jing
He, Jun
Chen, Lu-Yao
AuthorAffiliation 1 Department of HLA Laboratory, Jiangsu Institute of Hematology, First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215031, China
2 Collaborative Innovation Center of Hematology, Soochow University, Suzhou, Jiangsu 215006, China
AuthorAffiliation_xml – name: 1 Department of HLA Laboratory, Jiangsu Institute of Hematology, First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215031, China
– name: 2 Collaborative Innovation Center of Hematology, Soochow University, Suzhou, Jiangsu 215006, China
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Cites_doi 10.1111/tan.12536
10.1111/tan.12093
10.1038/sj.bmt.1703876
10.1038/s41409-019-0520-6
10.1016/j.humimm.2019.05.018
10.1371/journal.pone.0139485
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SubjectTerms Algorithms
Antigens
China
Clinical Observations
Genetics, Population
Haplotypes
HLA-A Antigens
HLA-B Antigens
HLA-C Antigens
HLA-DQ beta-Chains
HLA-DRB1 Chains - genetics
Humans
Motivation
Segregation
Software
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