Estimating time since infection in early homogeneous HIV-1 samples using a poisson model

Persistent Link:
http://hdl.handle.net/10150/610176
Title:
Estimating time since infection in early homogeneous HIV-1 samples using a poisson model
Author:
Giorgi, Elena; Funkhouser, Bob; Athreya, Gayathri; Perelson, Alan; Korber, Bette; Bhattacharya, Tanmoy
Affiliation:
Los Alamos National Laboratory, Los Alamos, NM 87545, USA; University of Massachusetts, Amherst, MA 01002, USA; University of Arizona, Tucson, AZ 85721, USA; The Santa Fe Institute, Santa Fe, NM 87501, USA
Issue Date:
2010
Publisher:
BioMed Central
Citation:
Giorgi et al. BMC Bioinformatics 2010, 11:532 http://www.biomedcentral.com/1471-2105/11/532
Journal:
BMC Bioinformatics
Rights:
© 2010 Giorgi et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0)
Collection Information:
This item is part of the UA Faculty Publications collection. For more information this item or other items in the UA Campus Repository, contact the University of Arizona Libraries at repository@u.library.arizona.edu.
Abstract:
BACKGROUND:The occurrence of a genetic bottleneck in HIV sexual or mother-to-infant transmission has been well documented. This results in a majority of new infections being homogeneous, i.e., initiated by a single genetic strain. Early after infection, prior to the onset of the host immune response, the viral population grows exponentially. In this simple setting, an approach for estimating evolutionary and demographic parameters based on comparison of diversity measures is a feasible alternative to the existing Bayesian methods (e.g., BEAST), which are instead based on the simulation of genealogies.RESULTS:We have devised a web tool that analyzes genetic diversity in acutely infected HIV-1 patients by comparing it to a model of neutral growth. More specifically, we consider a homogeneous infection (i.e., initiated by a unique genetic strain) prior to the onset of host-induced selection, where we can assume a random accumulation of mutations. Previously, we have shown that such a model successfully describes about 80% of sexual HIV-1 transmissions provided the samples are drawn early enough in the infection. Violation of the model is an indicator of either heterogeneous infections or the initiation of selection.CONCLUSIONS:When the underlying assumptions of our model (homogeneous infection prior to selection and fast exponential growth) are met, we are under a very particular scenario for which we can use a forward approach (instead of backwards in time as provided by coalescent methods). This allows for more computationally efficient methods to derive the time since the most recent common ancestor. Furthermore, the tool performs statistical tests on the Hamming distance frequency distribution, and outputs summary statistics (mean of the best fitting Poisson distribution, goodness of fit p-value, etc). The tool runs within minutes and can readily accommodate the tens of thousands of sequences generated through new ultradeep pyrosequencing technologies. The tool is available on the LANL website.
EISSN:
1471-2105
DOI:
10.1186/1471-2105-11-532
Version:
Final published version
Additional Links:
http://www.biomedcentral.com/1471-2105/11/532

Full metadata record

DC FieldValue Language
dc.contributor.authorGiorgi, Elenaen
dc.contributor.authorFunkhouser, Boben
dc.contributor.authorAthreya, Gayathrien
dc.contributor.authorPerelson, Alanen
dc.contributor.authorKorber, Betteen
dc.contributor.authorBhattacharya, Tanmoyen
dc.date.accessioned2016-05-20T09:00:21Z-
dc.date.available2016-05-20T09:00:21Z-
dc.date.issued2010en
dc.identifier.citationGiorgi et al. BMC Bioinformatics 2010, 11:532 http://www.biomedcentral.com/1471-2105/11/532en
dc.identifier.doi10.1186/1471-2105-11-532en
dc.identifier.urihttp://hdl.handle.net/10150/610176-
dc.description.abstractBACKGROUND:The occurrence of a genetic bottleneck in HIV sexual or mother-to-infant transmission has been well documented. This results in a majority of new infections being homogeneous, i.e., initiated by a single genetic strain. Early after infection, prior to the onset of the host immune response, the viral population grows exponentially. In this simple setting, an approach for estimating evolutionary and demographic parameters based on comparison of diversity measures is a feasible alternative to the existing Bayesian methods (e.g., BEAST), which are instead based on the simulation of genealogies.RESULTS:We have devised a web tool that analyzes genetic diversity in acutely infected HIV-1 patients by comparing it to a model of neutral growth. More specifically, we consider a homogeneous infection (i.e., initiated by a unique genetic strain) prior to the onset of host-induced selection, where we can assume a random accumulation of mutations. Previously, we have shown that such a model successfully describes about 80% of sexual HIV-1 transmissions provided the samples are drawn early enough in the infection. Violation of the model is an indicator of either heterogeneous infections or the initiation of selection.CONCLUSIONS:When the underlying assumptions of our model (homogeneous infection prior to selection and fast exponential growth) are met, we are under a very particular scenario for which we can use a forward approach (instead of backwards in time as provided by coalescent methods). This allows for more computationally efficient methods to derive the time since the most recent common ancestor. Furthermore, the tool performs statistical tests on the Hamming distance frequency distribution, and outputs summary statistics (mean of the best fitting Poisson distribution, goodness of fit p-value, etc). The tool runs within minutes and can readily accommodate the tens of thousands of sequences generated through new ultradeep pyrosequencing technologies. The tool is available on the LANL website.en
dc.language.isoenen
dc.publisherBioMed Centralen
dc.relation.urlhttp://www.biomedcentral.com/1471-2105/11/532en
dc.rights© 2010 Giorgi et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0)en
dc.titleEstimating time since infection in early homogeneous HIV-1 samples using a poisson modelen
dc.typeArticleen
dc.identifier.eissn1471-2105en
dc.contributor.departmentLos Alamos National Laboratory, Los Alamos, NM 87545, USAen
dc.contributor.departmentUniversity of Massachusetts, Amherst, MA 01002, USAen
dc.contributor.departmentUniversity of Arizona, Tucson, AZ 85721, USAen
dc.contributor.departmentThe Santa Fe Institute, Santa Fe, NM 87501, USAen
dc.identifier.journalBMC Bioinformaticsen
dc.description.collectioninformationThis item is part of the UA Faculty Publications collection. For more information this item or other items in the UA Campus Repository, contact the University of Arizona Libraries at repository@u.library.arizona.edu.en
dc.eprint.versionFinal published versionen
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