PMID- 24738646
OWN - NLM
STAT- MEDLINE
DCOM- 20141201
LR  - 20140417
IS  - 1399-0039 (Electronic)
IS  - 0001-2815 (Linking)
VI  - 83
IP  - 5
DP  - 2014 May
TI  - The HLA-net GENE[RATE] pipeline for effective HLA data analysis and its 
      application to 145 population samples from Europe and neighbouring areas.
PG  - 307-23
LID - 10.1111/tan.12356 [doi]
AB  - In this review, we present for the first time an integrated version of the 
      Gene[rate] computer tools which have been developed during the last 5 years to 
      analyse human leukocyte antigen (HLA) data in human populations, as well as the 
      results of their application to a large dataset of 145 HLA-typed population 
      samples from Europe and its two neighbouring areas, North Africa and West Asia, 
      now forming part of the Gene[va] database. All these computer tools and genetic 
      data are, from now, publicly available through a newly designed bioinformatics 
      platform, HLA-net, here presented as a main achievement of the HLA-NET scientific 
      programme. The Gene[rate] pipeline offers user-friendly computer tools to 
      estimate allele and haplotype frequencies, to test Hardy-Weinberg equilibrium 
      (HWE), selective neutrality and linkage disequilibrium, to recode HLA data, to 
      convert file formats, to display population frequencies of chosen alleles and 
      haplotypes in selected geographic regions, and to perform genetic comparisons 
      among chosen sets of population samples, including new data provided by the user. 
      Both numerical and graphical outputs are generated, the latter being highly 
      explicit and of publication quality. All these analyses can be performed on the 
      pipeline after scrupulous validation of the population sample's characterisation 
      and HLA typing reporting according to HLA-NET recommendations. The Gene[va] 
      database offers direct access to the HLA-A, -B, -C, -DQA1, -DQB1, -DRB1 and -DPB1 
      frequencies and summary statistics of 145 population samples having successfully 
      passed these HLA-NET 'filters', and representing three European subregions 
      (South-East, North-East and Central-West Europe) and two neighbouring areas 
      (North Africa, as far as Sudan, and West Asia, as far as South India). The 
      analysis of these data, summarized in this review, shows a substantial genetic 
      variation at the regional level in this continental area. These results have main 
      implications for population genetics, transplantation and epidemiological 
      studies.
CI  - (c) 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
FAU - Nunes, J M
AU  - Nunes JM
AD  - Laboratory of Anthropology, Genetics and Peopling History, Department of Genetics 
      and Evolution, Anthropology Unit and Institute of Genetics and Genomics in Geneva 
      (IGE3), University of Geneva, Geneva, Switzerland.
FAU - Buhler, S
AU  - Buhler S
FAU - Roessli, D
AU  - Roessli D
FAU - Sanchez-Mazas, A
AU  - Sanchez-Mazas A
CN  - HLA-net 2013 collaboration
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
PT  - Review
PL  - England
TA  - Tissue Antigens
JT  - Tissue antigens
JID - 0331072
RN  - 0 (HLA Antigens)
SB  - IM
MH  - Africa, Northern
MH  - *Alleles
MH  - Asia, Western
MH  - Computational Biology/instrumentation/*methods
MH  - Databases, Genetic
MH  - Europe
MH  - Gene Frequency
MH  - Genetic Linkage
MH  - Genetic Variation
MH  - HLA Antigens/classification/*genetics/immunology
MH  - Haplotypes
MH  - Histocompatibility Testing
MH  - Humans
MH  - Phylogeography
MH  - *Software
OTO - NOTNLM
OT  - Europe
OT  - GENE[RATE]
OT  - Gene[va]
OT  - HLA-net
OT  - North Africa
OT  - West Asia
OT  - data analysis
OT  - human leukocyte antigen
OT  - population genetics
FIR - Andreani, M
IR  - Andreani M
FIR - Benhamamouch, S
IR  - Benhamamouch S
FIR - Boldyreva, M
IR  - Boldyreva M
FIR - Canossi, A
IR  - Canossi A
FIR - Chiaroni, J
IR  - Chiaroni J
FIR - Darke, C
IR  - Darke C
FIR - Di Cristofaro, J
IR  - Di Cristofaro J
FIR - Dubois, V
IR  - Dubois V
FIR - Elamin, N
IR  - Elamin N
FIR - Eliaou, J-F
IR  - Eliaou JF
FIR - Fadhlaoui-Zid, K
IR  - Fadhlaoui-Zid K
FIR - Fischer, G F
IR  - Fischer GF
FIR - Grubic, Z
IR  - Grubic Z
FIR - Jaatinen, T
IR  - Jaatinen T
FIR - Kolesar, L
IR  - Kolesar L
FIR - Ligeiro, D
IR  - Ligeiro D
FIR - Lokki, M L
IR  - Lokki ML
FIR - Mehra, N
IR  - Mehra N
FIR - Nicoloso, G
IR  - Nicoloso G
FIR - Papaioannou Voniatis, D
IR  - Papaioannou Voniatis D
FIR - Papasteriades, C
IR  - Papasteriades C
FIR - Piancatelli, D
IR  - Piancatelli D
FIR - Poli, F
IR  - Poli F
FIR - Romon Alonso, I
IR  - Romon Alonso I
FIR - Slavcev, A
IR  - Slavcev A
FIR - Spiroski, M
IR  - Spiroski M
FIR - Spyropoulou-Vlachou, M
IR  - Spyropoulou-Vlachou M
FIR - Sulcebe, G
IR  - Sulcebe G
FIR - Suslova, T
IR  - Suslova T
FIR - Testi, M
IR  - Testi M
FIR - Tiercy, J-M
IR  - Tiercy JM
FIR - Toungouz Nevessignsky, M
IR  - Toungouz Nevessignsky M
FIR - Varnavidou-Nicolaidou, A
IR  - Varnavidou-Nicolaidou A
FIR - Vidan-Jeras, B
IR  - Vidan-Jeras B
EDAT- 2014/04/18 06:00
MHDA- 2014/12/15 06:00
CRDT- 2014/04/18 06:00
PHST- 2014/04/18 06:00 [entrez]
PHST- 2014/04/18 06:00 [pubmed]
PHST- 2014/12/15 06:00 [medline]
AID - 10.1111/tan.12356 [doi]
PST - ppublish
SO  - Tissue Antigens. 2014 May;83(5):307-23. doi: 10.1111/tan.12356.