PMID- 28697761
OWN - NLM
STAT- MEDLINE
DCOM- 20171101
LR  - 20221207
IS  - 1471-2105 (Electronic)
IS  - 1471-2105 (Linking)
VI  - 18
IP  - 1
DP  - 2017 Jul 11
TI  - HLA-check: evaluating HLA data from SNP information.
PG  - 334
LID - 10.1186/s12859-017-1746-1 [doi]
LID - 334
AB  - BACKGROUND: The major histocompatibility complex (MHC) region of the human 
      genome, and specifically the human leukocyte antigen (HLA) genes, play a major 
      role in numerous human diseases. With the recent progress of sequencing methods 
      (eg, Next-Generation Sequencing, NGS), the accurate genotyping of this region has 
      become possible but remains relatively costly. In order to obtain the HLA 
      information for the millions of samples already genotyped by chips in the past 
      ten years, efficient bioinformatics tools, such as SNP2HLA or HIBAG, have been 
      developed that infer HLA information from the linkage disequilibrium existing 
      between HLA alleles and SNP markers in the MHC region. RESULTS: In this study, we 
      first used ShapeIT and Impute2 to implement an imputation method akin to SNP2HLA 
      and found a comparable quality of imputation on a European dataset. More 
      importantly, we developed a new tool, HLA-check, that allows for the detection of 
      aberrant HLA allele calling with regard to the SNP genotypes in the region. 
      Adding this tool to the HLA imputation software increases dramatically their 
      accuracy, especially for HLA class I genes. CONCLUSION: Overall, HLA-check was 
      able to identify a limited number of implausible HLA typings (less than 10%) in a 
      population, and these samples can then either be removed or be retyped by NGS for 
      HLA association analysis.
FAU - Jeanmougin, Marc
AU  - Jeanmougin M
AD  - Laboratoire Genomique, Bioinformatique et Applications, EA 4627, Conservatoire 
      National des Arts et Metiers, 292 rue Saint-Martin, Paris, 75003, France.
FAU - Noirel, Josselin
AU  - Noirel J
AD  - Laboratoire Genomique, Bioinformatique et Applications, EA 4627, Conservatoire 
      National des Arts et Metiers, 292 rue Saint-Martin, Paris, 75003, France.
FAU - Coulonges, Cedric
AU  - Coulonges C
AD  - Laboratoire Genomique, Bioinformatique et Applications, EA 4627, Conservatoire 
      National des Arts et Metiers, 292 rue Saint-Martin, Paris, 75003, France.
FAU - Zagury, Jean-Francois
AU  - Zagury JF
AD  - Laboratoire Genomique, Bioinformatique et Applications, EA 4627, Conservatoire 
      National des Arts et Metiers, 292 rue Saint-Martin, Paris, 75003, France. 
      zagury@cnam.fr.
LA  - eng
PT  - Journal Article
DEP - 20170711
PL  - England
TA  - BMC Bioinformatics
JT  - BMC bioinformatics
JID - 100965194
RN  - 0 (HLA Antigens)
RN  - 0 (Histocompatibility Antigens Class I)
SB  - IM
MH  - Alleles
MH  - Genotyping Techniques/*methods
MH  - HLA Antigens/*genetics
MH  - Histocompatibility Antigens Class I/genetics
MH  - Histocompatibility Testing
MH  - Humans
MH  - Linkage Disequilibrium
MH  - *Polymorphism, Single Nucleotide
MH  - *Software
MH  - White People/genetics
PMC - PMC5504728
OTO - NOTNLM
OT  - Human leukocyte antigen
OT  - Imputation
OT  - Major histocompatibility complex
COIS- CONSENT FOR PUBLICATION: Not applicable. COMPETING INTERESTS: The authors declare 
      that they have no competing interests. PUBLISHER'S NOTE: Springer Nature remains 
      neutral with regard to jurisdictional claims in published maps and institutional 
      affiliations.
EDAT- 2017/07/13 06:00
MHDA- 2017/11/02 06:00
PMCR- 2017/07/11
CRDT- 2017/07/13 06:00
PHST- 2016/09/28 00:00 [received]
PHST- 2017/06/26 00:00 [accepted]
PHST- 2017/07/13 06:00 [entrez]
PHST- 2017/07/13 06:00 [pubmed]
PHST- 2017/11/02 06:00 [medline]
PHST- 2017/07/11 00:00 [pmc-release]
AID - 10.1186/s12859-017-1746-1 [pii]
AID - 1746 [pii]
AID - 10.1186/s12859-017-1746-1 [doi]
PST - epublish
SO  - BMC Bioinformatics. 2017 Jul 11;18(1):334. doi: 10.1186/s12859-017-1746-1.