Evidence map›Paper›PMID 15840174›Full record

ArticleBMC bioinformatics2005

Evolutionary distance estimation and fidelity of pair wise sequence alignment.

Michael S Rosenberg

Abstract read
In one paragraph

Article in BMC bioinformatics, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed.

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  17. New methods for inferring population dynamics from microbial sequences.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2007
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Michael S RosenbergCenter for Evolutionary Functional Genomics, The Biodesign Institute, and The School of Life Sciences, Arizona State University, Tempe, AZ 84287-4501, USA. msr@asu.edu

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEvolutionary distances are a critical measure in comparative genomics and molecular evolutionary biology. A simulation study was used to examine the effect of alignment accuracy of DNA sequences on evolutionary distance estimation.

resultsUnder the studied conditions, distance estimation was relatively unaffected by alignment error (50% or more of the sites incorrectly aligned) as long as 50% or more of the sites were identical among the sequences (observed P-distance < 0.5). Beyond this threshold, the alignment procedure artificially inflates the apparent sequence identity, skewing distance estimates, and creating alignments that are essentially indistinguishable from random data. This general result was independent of substitution model, sequence length, and insertion and deletion size and rate.

conclusionExamination of the estimated sequence identity may yield some guidance as to the accuracy of the alignment. Inaccurate alignments are expected to have large effects on analyses dependent on site specificity, but analyses that depend on evolutionary distance may be somewhat robust to alignment error as long as fewer than half of the sites have diverged.

Indexed as

AlgorithmsAnimalsBiological EvolutionCluster AnalysisComputational BiologyComputer SimulationDatabases, ProteinEvolution, MolecularGene DeletionGenomicsHumansModels, GeneticModels, MolecularPattern Recognition, AutomatedPhylogenyProteinsProteins

Identifiers

PMID15840174
PMCPMC1087827

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.