Mitigating scoring errors in microsatellite data from wild populations

Microsatellite data are widely used to test ecological and evolutionary hypotheses in wild populations. In this paper, we consider three typical sources of scoring errors capable of biasing biological conclusions: stuttering, large-allele dropout and null alleles. We describe methods to detect error...

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Bibliographic Details
Published in:	Molecular ecology notes Vol. 6; no. 4; pp. 951 - 957
Main Authors:	DEWOODY, JENNIFER, NASON, JOHN D, HIPKINS, VALERIE D
Format:	Journal Article
Language:	English
Published:	Oxford, UK Oxford, UK : Blackwell Publishing Ltd 01-12-2006 Blackwell Publishing Ltd
Subjects:	alleles data analysis genetic markers large allele dropout literature reviews loci microsatellite microsatellite repeats null alleles polymerase chain reaction population genetics scoring errors SSR stuttering wild populations
Online Access:	Get full text
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Summary:	Microsatellite data are widely used to test ecological and evolutionary hypotheses in wild populations. In this paper, we consider three typical sources of scoring errors capable of biasing biological conclusions: stuttering, large-allele dropout and null alleles. We describe methods to detect errors and propose conventions to mitigate scoring errors and report error rates in studies of wild populations. Finally, we discuss potential bias in ecological or evolutionary conclusions based on data sets containing these scoring errors.
Bibliography:	http://dx.doi.org/10.1111/j.1471-8286.2006.01449.x http://hdl.handle.net/10113/31698 ArticleID:MEN1449 istex:9C4C83A69CE13B06A08E77E9D8536E894C398876 ark:/67375/WNG-D8N3H4G7-F
ISSN:	1471-8278 1471-8286
DOI:	10.1111/j.1471-8286.2006.01449.x