Evidence map›Paper›PMID 19015730›Full record

ArticlePloS one2008

The trouble with sliding windows and the selective pressure in BRCA1.

Karl Schmid, Ziheng Yang

Erratum issuedAbstract read
In one paragraph

Article in PloS one, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

26 citing papers in PubMed.

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4 · The record

Corrections and comments

  • Erratum issued
5 · Who and what money

Authors and funding

2 authors.

Karl SchmidDepartment of Plant Biology and Forest Genetics, Swedish University of Agricultural Sciences (SLU), Uppsala, Sweden.
Ziheng Yang

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sliding-window analysis has widely been used to uncover synonymous (silent, d(S)) and nonsynonymous (replacement, d(N)) rate variation along the protein sequence and to detect regions of a protein under selective constraint (indicated by d(N)<d(S)) or positive selection (indicated by d(N)>d(S)). The approach compares two or more protein-coding genes and plots estimates d(/\)(S) and d(/\)(N) from each sliding window along the sequence. Here we demonstrate that the approach produces artifactual trends of synonymous and nonsynonymous rate variation, with greater variation in d(/\)(S) than in d(/\)(N). Such trends are generated even if the true d(S) and d(N) are constant along the whole protein and different codons are evolving independently. Many published tests of negative and positive selection using sliding windows that we have examined appear to be invalid because they fail to correct for multiple testing. Instead, likelihood ratio tests provide a more rigorous framework for detecting signals of natural selection affecting protein evolution. We demonstrate that a previous finding that a particular region of the BRCA1 gene experienced a synonymous rate reduction driven by purifying selection is likely an artifact of the sliding window analysis. We evaluate various sliding-window analyses in molecular evolution, population genetics, and comparative genomics, and argue that the approach is not generally valid if it is not known a priori that a trend exists and if no correction for multiple testing is applied.

Indexed as

Genes, BRCA1Genetic TechniquesAnimalsBRCA1 ProteinComputer SimulationDatabases, GeneticEvolution, MolecularFalse Positive ReactionsGenetics, PopulationHumansLikelihood FunctionsModels, StatisticalPhylogenyPressureSelection, GeneticBRCA1 ProteinBRCA1 protein, human

Identifiers

PMID19015730
PMCPMC2581807

What OpenQuestion holds

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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.