PMID- 25183223
OWN - NLM
STAT- MEDLINE
DCOM- 20141108
LR  - 20240321
IS  - 1471-2105 (Electronic)
IS  - 1471-2105 (Linking)
VI  - 15
IP  - 1
DP  - 2014 Sep 3
TI  - A fault-tolerant method for HLA typing with PacBio data.
PG  - 296
LID - 10.1186/1471-2105-15-296 [doi]
LID - 296
AB  - BACKGROUND: Human leukocyte antigen (HLA) genes are critical genes involved in 
      important biomedical aspects, including organ transplantation, autoimmune 
      diseases and infectious diseases. The gene family contains the most polymorphic 
      genes in humans and the difference between two alleles is only a single base pair 
      substitution in many cases. The next generation sequencing (NGS) technologies 
      could be used for high throughput HLA typing but in silico methods are still 
      needed to correctly assign the alleles of a sample. Computer scientists have 
      developed such methods for various NGS platforms, such as Illumina, Roche 454 and 
      Ion Torrent, based on the characteristics of the reads they generate. However, 
      the method for PacBio reads was less addressed, probably owing to its high error 
      rates. The PacBio system has the longest read length among available NGS 
      platforms, and therefore is the only platform capable of having exon 2 and exon 3 
      of HLA genes on the same read to unequivocally solve the ambiguity problem caused 
      by the "phasing" issue. RESULTS: We proposed a new method BayesTyping1 to assign 
      HLA alleles for PacBio circular consensus sequencing reads using Bayes' theorem. 
      The method was applied to simulated data of the three loci HLA-A, HLA-B and 
      HLA-DRB1. The experimental results showed its capability to tolerate the 
      disturbance of sequencing errors and external noise reads. CONCLUSIONS: The 
      BayesTyping1 method could overcome the problems of HLA typing using PacBio reads, 
      which mostly arise from sequencing errors of PacBio reads and the divergence of 
      HLA genes, to some extent.
FAU - Chang, Chia-Jung
AU  - Chang CJ
FAU - Chen, Pei-Lung
AU  - Chen PL
FAU - Yang, Wei-Shiung
AU  - Yang WS
FAU - Chao, Kun-Mao
AU  - Chao KM
AD  - Department of Computer Science and Information Engineering, National Taiwan 
      University, No,1, Sec,4, Roosevelt Road, Taipei 10617, Taiwan. 
      kmchao@csie.ntu.edu.tw.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20140903
PL  - England
TA  - BMC Bioinformatics
JT  - BMC bioinformatics
JID - 100965194
RN  - 0 (HLA Antigens)
SB  - IM
MH  - Alleles
MH  - Bayes Theorem
MH  - Computational Biology/*methods
MH  - Exons/genetics
MH  - Genotyping Techniques/*methods
MH  - HLA Antigens/*genetics
MH  - High-Throughput Nucleotide Sequencing
MH  - Humans
MH  - Polymorphism, Genetic
MH  - Sequence Analysis, DNA
PMC - PMC4161847
EDAT- 2014/09/04 06:00
MHDA- 2014/11/09 06:00
PMCR- 2014/09/03
CRDT- 2014/09/04 06:00
PHST- 2014/06/03 00:00 [received]
PHST- 2014/08/26 00:00 [accepted]
PHST- 2014/09/04 06:00 [entrez]
PHST- 2014/09/04 06:00 [pubmed]
PHST- 2014/11/09 06:00 [medline]
PHST- 2014/09/03 00:00 [pmc-release]
AID - 1471-2105-15-296 [pii]
AID - 6558 [pii]
AID - 10.1186/1471-2105-15-296 [doi]
PST - epublish
SO  - BMC Bioinformatics. 2014 Sep 3;15(1):296. doi: 10.1186/1471-2105-15-296.