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Titolo:
An efficient test for comparing sequence diversity between two populations
Autore:
Gilbert, PB; Novitsky, VA; Montano, MA; Essex, M;
Indirizzi:
Harvard Univ, Sch Publ Hlth, Ctr Biostat AIDS Res, Boston, MA 02115 USA Harvard Univ Boston MA USA 02115 r Biostat AIDS Res, Boston, MA 02115 USA Harvard Univ, Sch Publ Hlth, Dept Biostat, Boston, MA 02115 USA Harvard Univ Boston MA USA 02115 Hlth, Dept Biostat, Boston, MA 02115 USA Harvard Univ, Sch Publ Hlth, Harvard AIDS Inst, Boston, MA 02115 USA Harvard Univ Boston MA USA 02115 Harvard AIDS Inst, Boston, MA 02115 USA Harvard Univ, Sch Publ Hlth, Dept Immunol & Infect Dis, Boston, MA 02115 USA Harvard Univ Boston MA USA 02115 munol & Infect Dis, Boston, MA 02115 USA
Titolo Testata:
JOURNAL OF COMPUTATIONAL BIOLOGY
fascicolo: 2, volume: 8, anno: 2001,
pagine: 123 - 139
SICI:
1066-5277(2001)8:2<123:AETFCS>2.0.ZU;2-B
Fonte:
ISI
Lingua:
ENG
Soggetto:
IMMUNODEFICIENCY-VIRUS TYPE-1; VACCINE DEVELOPMENT; HIV-1 SUBTYPES; AFRICA; TRIALS; DNA; TRANSMISSION; INFECTION; EVOLUTION; MODELS;
Keywords:
HIV genetic diversity; HIV vaccine design; statistical hypothesis testing; two-sample test; U-statistic;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Life Sciences
Citazioni:
37
Recensione:
Indirizzi per estratti:
Indirizzo: Gilbert, PB Harvard Univ, Sch Publ Hlth, Ctr Biostat AIDS Res, 665 Huntington Ave, Boston, MA 02115 USA Harvard Univ 665 Huntington Ave Boston MA USA02115 02115 USA
Citazione:
P.B. Gilbert et al., "An efficient test for comparing sequence diversity between two populations", J COMPUT BI, 8(2), 2001, pp. 123-139

Abstract

We address the problem of comparing interindividual genomic sequence diversity between two populations. Although the methods are general, for concreteness we focus on comparing two human immunodeficiency virus (HIV) infectedpopulations. From a viral isolate(s) taken from each individual in a sample of persons from each population, suppose one or multiple measurements aremade on the genetic sequence of a coding region of HIV. Given a definitionof genetic distance between sequences, the goal is to test if the distribution of interindividual distances differs between populations. If distancesbetween all pairs of sequences within each group are used, then data-dependencies arising from the use of multiple sequences from individuals invalidates the use of a standard two-sample test such as the t-test. Where this problem has been recognized, a typical solution has been to apply a standardtest to a reduced dataset comprised of one sequence or a consensus sequence from each patient. Disadvantages of this procedure are that the conclusion of the test depends on the choice of utilized sequences, often an arbitrary decision, and exclusion of replicate sequences from the analysis may needlessly sacrifice statistical power. We present a new test free of these drawbacks, which is based on a statistic that linearly combines all possible standard test statistics calculated from independent sequence subsamples. We describe statistical power advantages of the test and illustrate its use by application to nucleotide sequence distances measured from HIV-1 infected populations in southern Africa (GenBank accession numbers AF110959-AF110981) and North America/Europe. The test makes minimal assumptions, is maximally efficient and objective, and is broadly applicable.

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Documento generato il 18/09/20 alle ore 11:13:56