Micro-Checker: Software for identifying and correcting genotyping errors in microsatellite data

By Cock van Oosterhout, W. Hutchinson, Derek P. M. Wills, P. Shipley. 2004

10,696 citations recorded by the source corpus.

DNA degradation, low DNA concentrations and primer-site mutations may result in the incorrect assignment of microsatellite genotypes, potentially biasing population genetic analyses. MICRO - CHECKER is WINDOWS ®-based software that tests the genotyping of microsatellites from diploid populations. The program aids identification of genotyping errors due to nonamplified alleles (null alleles), short allele dominance (large allele dropout) and the scoring of stutter peaks, and also detects typographic errors. MICRO - CHECKER estimates the frequency of null alleles and, importantly, can adjust the allele and genotype frequencies of the amplified alleles, permitting their use in further population genetic analysis. MICRO CHECKER can be freely downloaded from http://www.microchecker.hull.ac.uk/.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/97009659427c57d581215f58dead922b0328c345

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Citations in the corpus

Genetic isolation by distance and localized fjord population structure in Pacific cod (Gadus macrocephalus): limited effective dispersal in the northeastern Pacific Ocean (2009, methodology): “The program MICRO-CHECKER 2.2.3 ( van Oosterhout et al. 2004 ) was used to check for the presence of null alleles, scoring errors, stuttering, and large allele dropout.”
Hybridisation between native Oreochromis species and introduced Nile tilapia O. niloticus in the Kafue River, Zambia (2014, methodology): “Second, we tested for the possible presence of null alleles using Arlequin 3.5 (Excoffier and Lischer 2010) and the program Microchecker (van Oosterhout et al. 2004) to test all loci in each population, employing the Brookfield-1 equation (Brookfield 1996).”
Phylogeography and genetic differentiation along the distributional range of the orchid Epidendrum fulgens: a Neotropical coastal species not restricted to glacial refugia (2011, methodology): “The microsatellite data were tested for genotyping errors resulting from stuttering, short allele dominance and null alleles using a Monte Carlo simulation of expected allele-size differences implemented in micro-checker 2.2.3 (van Oosterhout et al., 2004).”
Global warming will affect the genetic diversity and uniqueness of Lycaena helle populations (2011, methodology): “Distortions of our results obtained by microsatellites through stutter bands, large allele dropout or null alleles (cf. Selkoe & Toonen, 2006) were tested using the programme Micro-Checker (Van Oosterhout et al., 2004).”
Effects of roads on patterns of genetic differentiation in red-backed salamanders, Plethodon cinereus (2008, methodology): “W equilibrium after the Bonferroni correction, we used Microchecker 2.2.3 (van Oosterhout et al. 2004) to check for evidence of null alleles, allelic dropouts, or mis-scoring.”
Microsatellites for ecologists: a practical guide to using and evaluating microsatellite markers. (2006, methodology): “More complex and realistic mutational models that add the probability of non-stepwise mutation to the SMM are beginning to replace the SMM in common genetic analyses, and are already available in several statistical packages (e.g. Piry et al. 1999; Van Oosterhout et al. 2004).”
Congruence between environmental parameters, morphology and genetic structure in Australia’s most widely distributed eucalypt, Eucalyptus camaldulensis (2008, methodology): “Null allele frequencies were estimated using the method of Brookfield in the MICRO-CHECKER package (Oosterhout et al. 2004).”
Why some species of birds do not avoid inbreeding: insights from New Zealand robins and saddlebacks (2009, positive): “MicroChecker (Van Oosterhout et al. 2004) was used to determine the likelihood of large allele dropout, null alleles, and scoring error due to stuttering.”
Population structure and conservation implications for the loggerhead sea turtle of the Cape Verde Islands (2010, methodology): “The MICRO-CHECKER software (Van Oosterhout et al. 2004) indicated the possible presence of null alleles and/or stuttering at this locus, which could explain the deviation from HW equilibrium.”
Landscape genetics of the Alpine newt (Mesotriton alpestris) inferred from a strip-based approach (2011, background): “wetlands) induced by anthropogenic activities (Blaustein et al. 1994), as they are generally characterized by strong annual population fluctuations (Meyer et al. 1998; Trenham et al. 2003 ), high site fidelity (Smith and Green 2005) and poor ground-dispersal abilities (Sinsch 1990).”
Genetic diversity and structure of local apple cultivars from Northeastern Spain assessed by microsatellite markers (2012, neutral): “2.2.3 software (van Oosterhout et al. 2004).”
Genetic diversity and population structure of the Chinese mitten crab Eriocheir sinensis in its native range (2009, methodology): “Raw data were checked for scoring errors due to stuttering, larger allele dropout, or null alleles using the program MICRO-CHECKER 2.2.3 (Van Oosterhout et al. 2004).”
Glacial survival and post‐glacial recolonization of an arctic–alpine freshwater insect (Arcynopteryx dichroa, Plecoptera, Perlodidae) in Europe (2013, methodology): “Loci were scored using the software genemapper 4.0 (Applied Biosystems) and were analysed for possible null alleles using microchecker 2.2.3 (van Oosterhout et al., 2004) for each sampling site.”
Detecting interspecific and geographic differentiation patterns in two interfertile oak species (Quercus petraea (Matt.) Liebl. and Q. robur L.) using small sets of microsatellite markers. (2010, methodology): “Data Analysis 36 37 First, we controlled our data for possible scoring errors and occurrence of null (non-38 amplifiable) alleles using the software Microchecker (Van Oosterhout et al., 2004).”