PMID- 29326702
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20191120
IS  - 1664-3224 (Print)
IS  - 1664-3224 (Electronic)
IS  - 1664-3224 (Linking)
VI  - 8
DP  - 2017
TI  - Accuracy of Programs for the Determination of Human Leukocyte Antigen Alleles 
      from Next-Generation Sequencing Data.
PG  - 1815
LID - 10.3389/fimmu.2017.01815 [doi]
LID - 1815
AB  - The human leukocyte antigen (HLA) genes code for proteins that play a central 
      role in the function of the immune system by presenting peptide antigens to T 
      cells. As HLA genes show extremely high genetic polymorphism, HLA typing at the 
      allele level is demanding and is based on DNA sequencing. Determination of HLA 
      alleles is warranted as HLA alleles are major genetic risk factors in autoimmune 
      diseases and are matched in transplantation. Here, we compared the accuracy of 
      several published HLA-typing algorithms that are based on next-generation 
      sequencing (NGS) data. As genome sequencing is becoming increasingly common in 
      research, we wanted to test how well HLA alleles can be deduced from genome data 
      produced in studies with objectives other than HLA typing and in platforms not 
      especially designed for HLA typing. The accuracies were assessed using datasets 
      consisting of NGS data produced using an in-house sequencing platform, including 
      the full 4 Mbp HLA segment, from 94 stem cell transplantation patients and exome 
      sequences from 63 samples of the 1000 Genomes collection. In the patient dataset, 
      none of the software gave perfect results for all the samples and genes when 
      programs were used with the default settings. However, we found that ensemble 
      prediction of the results or modifications of the settings could be used to 
      improve accuracy. For the exome-only data, most of the algorithms did not perform 
      very well. The results indicate that the use of these algorithms for accurate HLA 
      allele determination is not straightforward when based on NGS data not especially 
      targeted to the HLA typing and their accurate use requires HLA expertise.
FAU - Larjo, Antti
AU  - Larjo A
AD  - Finnish Red Cross Blood Service, Helsinki, Finland.
FAU - Eveleigh, Robert
AU  - Eveleigh R
AD  - McGill University and Genome Quebec Innovation Centre, Montreal, QC, Canada.
FAU - Kilpelainen, Elina
AU  - Kilpelainen E
AD  - Finnish Red Cross Blood Service, Helsinki, Finland.
FAU - Kwan, Tony
AU  - Kwan T
AD  - McGill University and Genome Quebec Innovation Centre, Montreal, QC, Canada.
FAU - Pastinen, Tomi
AU  - Pastinen T
AD  - McGill University and Genome Quebec Innovation Centre, Montreal, QC, Canada.
FAU - Koskela, Satu
AU  - Koskela S
AD  - Finnish Red Cross Blood Service, Helsinki, Finland.
FAU - Partanen, Jukka
AU  - Partanen J
AD  - Finnish Red Cross Blood Service, Helsinki, Finland.
LA  - eng
PT  - Journal Article
DEP - 20171213
PL  - Switzerland
TA  - Front Immunol
JT  - Frontiers in immunology
JID - 101560960
PMC - PMC5733459
OTO - NOTNLM
OT  - genetic variation
OT  - genome sequence
OT  - histocompatibility
OT  - human leukocyte antigen alleles
OT  - transplantation
EDAT- 2018/01/13 06:00
MHDA- 2018/01/13 06:01
PMCR- 2017/01/01
CRDT- 2018/01/13 06:00
PHST- 2017/07/11 00:00 [received]
PHST- 2017/12/01 00:00 [accepted]
PHST- 2018/01/13 06:00 [entrez]
PHST- 2018/01/13 06:00 [pubmed]
PHST- 2018/01/13 06:01 [medline]
PHST- 2017/01/01 00:00 [pmc-release]
AID - 10.3389/fimmu.2017.01815 [doi]
PST - epublish
SO  - Front Immunol. 2017 Dec 13;8:1815. doi: 10.3389/fimmu.2017.01815. eCollection 
      2017.