Pironti, Alejandro, Sierra, Saleta, Kaiser, Rolf, Lengauer, Thomas ORCID: 0000-0003-3801-2640 and Pfeifer, Nico ORCID: 0000-0002-4647-8566 (2015). Effects of sequence alterations on results from genotypic tropism testing. J. Clin. Virol., 65. S. 68 - 74. AMSTERDAM: ELSEVIER SCIENCE BV. ISSN 1873-5967

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Abstract

Background: geno2pheno([coreceptor]) is a bioinformatic method for genotypic tropism determination (GTD) which has been extensively validated. Objectives: GTD can be affected by sequencing/base-calling variability and unreliable representation of minority populations in Sanger bulk sequencing. This study aims at quantifying the robustness of geno2pheno([coreceptor]) with respect to these issues. GTD with a single amplification or in triplicate (henceforth singleton/triplicate) is considered. Study Design: From a dataset containing 67,997HIV-1 V3 nucleotide sequences, two datasets simulating sequencing variability were created. Further two datasets were created to simulate unreliable representation of minority variants. After interpretation of all sequences with geno2pheno[coreceptor], probabilities of change of predicted tropism were calculated. Results: geno2pheno([coreceptor]) tends to report reduced false-positive rates (FPRs) when sequence alterations are present. Triplicate FPRs tend to be lower than singleton FPRs, resulting in a bias towards classifying viruses as X4-capable. Alterations introduced into nucleotide sequences by simulation change singleton predicted tropism with a probability <= 2%. Triplicate prediction lowers this probability for predicted X4 tropism, but raises it for predicted R5 tropism <= 6%. Simulated limited detection of minority variants in X4 sequences resulted in unchanged predicted tropism with probability above 90% as compared to probability above 98% with triplicate FPRs. Conclusions: geno2pheno([coreceptor]) proved to be robust when sequence alterations are present and when detectable minorities are missed by bulk sequencing. Changes in tropism prediction due to sequence alterations as well as triplicate prediction are much more likely to result in false X4-capable predictions than in false R5 predictions. (C) 2015 Published by Elsevier B.V.

Item Type: Journal Article
Creators:
CreatorsEmailORCIDORCID Put Code
Pironti, AlejandroUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Sierra, SaletaUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Kaiser, RolfUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Lengauer, ThomasUNSPECIFIEDorcid.org/0000-0003-3801-2640UNSPECIFIED
Pfeifer, NicoUNSPECIFIEDorcid.org/0000-0002-4647-8566UNSPECIFIED
URN: urn:nbn:de:hbz:38-408311
DOI: 10.1016/j.jcv.2015.02.006
Journal or Publication Title: J. Clin. Virol.
Volume: 65
Page Range: S. 68 - 74
Date: 2015
Publisher: ELSEVIER SCIENCE BV
Place of Publication: AMSTERDAM
ISSN: 1873-5967
Language: English
Faculty: Faculty of Mathematics and Natural Sciences
Divisions: Faculty of Mathematics and Natural Sciences > Department of Mathematics and Computer Science > Institute of Computer Science
Subjects: no entry
Uncontrolled Keywords:
KeywordsLanguage
HIV; PREDICTION; TROFILE; ASSAYMultiple languages
VirologyMultiple languages
Refereed: Yes
URI: http://kups.ub.uni-koeln.de/id/eprint/40831

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