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Detecting Microsatellites in Genome Data: Variance in Definitions and Bioinformatic Approaches Cause Systematic Bias

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...

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Detalles Bibliográficos
Autores principales: Merkel, Angelika, Gemmell, Neil J.
Formato: Texto
Lenguaje:English
Publicado: Libertas Academica 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2614199/
https://www.ncbi.nlm.nih.gov/pubmed/19204802
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author Merkel, Angelika
Gemmell, Neil J.
author_facet Merkel, Angelika
Gemmell, Neil J.
author_sort Merkel, Angelika
collection PubMed
description 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
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spelling pubmed-26141992009-02-09 Detecting Microsatellites in Genome Data: Variance in Definitions and Bioinformatic Approaches Cause Systematic Bias Merkel, Angelika Gemmell, Neil J. Evol Bioinform Online Original Research 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 Libertas Academica 2008-02-09 /pmc/articles/PMC2614199/ /pubmed/19204802 Text en Copyright © 2008 The authors. http://creativecommons.org/licenses/by/3.0 This article is published under the Creative Commons Attribution By licence. For further information go to: http://creativecommons.org/licenses/by/3.0. (http://creativecommons.org/licenses/by/3.0)
spellingShingle Original Research
Merkel, Angelika
Gemmell, Neil J.
Detecting Microsatellites in Genome Data: Variance in Definitions and Bioinformatic Approaches Cause Systematic Bias
title Detecting Microsatellites in Genome Data: Variance in Definitions and Bioinformatic Approaches Cause Systematic Bias
title_full Detecting Microsatellites in Genome Data: Variance in Definitions and Bioinformatic Approaches Cause Systematic Bias
title_fullStr Detecting Microsatellites in Genome Data: Variance in Definitions and Bioinformatic Approaches Cause Systematic Bias
title_full_unstemmed Detecting Microsatellites in Genome Data: Variance in Definitions and Bioinformatic Approaches Cause Systematic Bias
title_short Detecting Microsatellites in Genome Data: Variance in Definitions and Bioinformatic Approaches Cause Systematic Bias
title_sort detecting microsatellites in genome data: variance in definitions and bioinformatic approaches cause systematic bias
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2614199/
https://www.ncbi.nlm.nih.gov/pubmed/19204802
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