Evidence map›Paper›PMID 19204802›Full record

ArticleEvolutionary bioinformatics online2008

Detecting microsatellites in genome data: variance in definitions and bioinformatic approaches cause systematic bias.

Angelika Merkel, Neil J Gemmell

Abstract read
In one paragraph

Article in Evolutionary bioinformatics online, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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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

2 authors.

Angelika MerkelSchool of Biological Sciences, University of Canterbury, Christchurch, New Zealand. ame52@student.canterbury.ac.nz
Neil J Gemmell

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microsatellites are currently one of the most commonly used genetic markers. The application of bioinformatic tools has become common practice in the study of these short tandem repeats (STR). However, in silico studies can suffer from study bias. Using a meta-analysis on microsatellite distribution in yeast we show that estimates of numbers of repeats reported by different studies can differ in the order of several magnitudes, even within a single genome. These differences arise because varying definitions of microsatellites, spanning repeat size, array length and array composition, are used in different search paradigms, with minimum array length being the main influencing factor. Structural differences in the implemented search algorithm additionally contribute to variation in the number of repeats detected. We suggest that for future studies a consistent approach to STR searches is adopted in order to improve the power of intra- and interspecific comparisons.

Indexed as

array lengthdefinitiongenomemicrosatellitesshort tandem repeatsstudy bias

Identifiers

PMID19204802
PMCPMC2614199

What OpenQuestion holds

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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.