jpHMM: improving the reliability of recombination prediction in HIV-1.
Previously, we developed jumping profile hidden Markov model (jpHMM), a new method to detect recombinations in HIV-1 genomes. The jpHMM predicts recombination breakpoints in a query sequence and assigns to each position of the sequence one of the major HIV-1 subtypes. Since incorrect subtype assignment or recombination prediction may lead to wrong conclusions in epidemiological or vaccine research, information about the reliability of the predicted parental subtypes and breakpoint positions is valuable. For this reason, we extended the output of jpHMM to include such information in terms of 'uncertainty' regions in the recombination prediction and an interval estimate of the breakpoint. Both types of information are computed based on the posterior probabilities of the subtypes at each query sequence position. Our results show that this extension strongly improves the reliability of the jpHMM recombination prediction. The jpHMM is available online at http://jphmm.gobics.de/.
Schultz
Anne-Kathrin
AK
Institut für Mikrobiologie und Genetik, Abteilung für Bioinformatik, Georg-August-Universität Göttingen, Goldschmidtstr. 1, 37077, Göttingen, Germany.
Zhang
Ming
M
Bulla
Ingo
I
Leitner
Thomas
T
Korber
Bette
B
Morgenstern
Burkhard
B
Stanke
Mario
M
D001483:Base Sequence; D053960:DNA Breaks; D015497:HIV-1 / Q000145:classification* / Q000235:genetics*; D020407:Internet; D008390:Markov Chains; D010802:Phylogeny; D011995:Recombination, Genetic; D015203:Reproducibility of Results; D016415:Sequence Alignment; D012984:Software