Data from: Reliability assessment of null allele detection: inconsistencies between and within different methods

Microsatellite loci are widely used in population genetic studies, but the presence of null alleles may lead to biased results. Here, we assessed five methods that indirectly detect null alleles and found large inconsistencies among them. Our analysis was based on 20 microsatellite loci genotyped in...

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Main Authors: Dąbrowski, Michal J., Pilot, Malgorzata, Kruczyk, Marcin, Żmihorski, Michal, Umer, Husen M., Gliwicz, Joanna
Format: Other/Unknown Material
Language:unknown
Published: Zenodo 2013
Subjects:
Online Access:https://doi.org/10.5061/dryad.4p41m
id ftzenodo:oai:zenodo.org:4998761
record_format openpolar
spelling ftzenodo:oai:zenodo.org:4998761 2024-09-15T18:39:52+00:00 Data from: Reliability assessment of null allele detection: inconsistencies between and within different methods Dąbrowski, Michal J. Pilot, Malgorzata Kruczyk, Marcin Żmihorski, Michal Umer, Husen M. Gliwicz, Joanna 2013-09-20 https://doi.org/10.5061/dryad.4p41m unknown Zenodo https://doi.org/10.1111/1755-0998.12177 https://zenodo.org/communities/dryad https://doi.org/10.5061/dryad.4p41m oai:zenodo.org:4998761 info:eu-repo/semantics/openAccess Creative Commons Zero v1.0 Universal https://creativecommons.org/publicdomain/zero/1.0/legalcode Rodentia genotypes root vole genotyping errors Microtus oeconomus Heterozygosity simulated genotypes tundra vole Arvicolidae null alleles natural populations info:eu-repo/semantics/other 2013 ftzenodo https://doi.org/10.5061/dryad.4p41m10.1111/1755-0998.12177 2024-07-25T13:36:47Z Microsatellite loci are widely used in population genetic studies, but the presence of null alleles may lead to biased results. Here, we assessed five methods that indirectly detect null alleles and found large inconsistencies among them. Our analysis was based on 20 microsatellite loci genotyped in a natural population of Microtus oeconomus sampled during 8 years, together with 1200 simulated populations without null alleles, but experiencing bottlenecks of varying duration and intensity, and 120 simulated populations with known null alleles. In the natural population, 29% of positive results were consistent between the methods in pairwise comparisons, and in the simulated data set, this proportion was 14%. The positive results were also inconsistent between different years in the natural population. In the null-allele-free simulated data set, the number of false positives increased with increased bottleneck intensity and duration. We also found a low concordance in null allele detection between the original simulated populations and their 20% random subsets. In the populations simulated to include null alleles, between 22% and 42% of true null alleles remained undetected, which highlighted that detection errors are not restricted to false positives. None of the evaluated methods clearly outperformed the others when both false-positive and false-negative rates were considered. Accepting only the positive results consistent between at least two methods should considerably reduce the false-positive rate, but this approach may increase the false-negative rate. Our study demonstrates the need for novel null allele detection methods that could be reliably applied to natural populations. Genotypes_data The file Genotypes_data.zip contains two folders: Simulated_genotypes, Simulated_genotypes_subpopulations and one .csv file named Microtus_oeconomus_genotypes.csv Other/Unknown Material Tundra Zenodo
institution Open Polar
collection Zenodo
op_collection_id ftzenodo
language unknown
topic Rodentia
genotypes
root vole
genotyping errors
Microtus oeconomus
Heterozygosity
simulated genotypes
tundra vole
Arvicolidae
null alleles
natural populations
spellingShingle Rodentia
genotypes
root vole
genotyping errors
Microtus oeconomus
Heterozygosity
simulated genotypes
tundra vole
Arvicolidae
null alleles
natural populations
Dąbrowski, Michal J.
Pilot, Malgorzata
Kruczyk, Marcin
Żmihorski, Michal
Umer, Husen M.
Gliwicz, Joanna
Data from: Reliability assessment of null allele detection: inconsistencies between and within different methods
topic_facet Rodentia
genotypes
root vole
genotyping errors
Microtus oeconomus
Heterozygosity
simulated genotypes
tundra vole
Arvicolidae
null alleles
natural populations
description Microsatellite loci are widely used in population genetic studies, but the presence of null alleles may lead to biased results. Here, we assessed five methods that indirectly detect null alleles and found large inconsistencies among them. Our analysis was based on 20 microsatellite loci genotyped in a natural population of Microtus oeconomus sampled during 8 years, together with 1200 simulated populations without null alleles, but experiencing bottlenecks of varying duration and intensity, and 120 simulated populations with known null alleles. In the natural population, 29% of positive results were consistent between the methods in pairwise comparisons, and in the simulated data set, this proportion was 14%. The positive results were also inconsistent between different years in the natural population. In the null-allele-free simulated data set, the number of false positives increased with increased bottleneck intensity and duration. We also found a low concordance in null allele detection between the original simulated populations and their 20% random subsets. In the populations simulated to include null alleles, between 22% and 42% of true null alleles remained undetected, which highlighted that detection errors are not restricted to false positives. None of the evaluated methods clearly outperformed the others when both false-positive and false-negative rates were considered. Accepting only the positive results consistent between at least two methods should considerably reduce the false-positive rate, but this approach may increase the false-negative rate. Our study demonstrates the need for novel null allele detection methods that could be reliably applied to natural populations. Genotypes_data The file Genotypes_data.zip contains two folders: Simulated_genotypes, Simulated_genotypes_subpopulations and one .csv file named Microtus_oeconomus_genotypes.csv
format Other/Unknown Material
author Dąbrowski, Michal J.
Pilot, Malgorzata
Kruczyk, Marcin
Żmihorski, Michal
Umer, Husen M.
Gliwicz, Joanna
author_facet Dąbrowski, Michal J.
Pilot, Malgorzata
Kruczyk, Marcin
Żmihorski, Michal
Umer, Husen M.
Gliwicz, Joanna
author_sort Dąbrowski, Michal J.
title Data from: Reliability assessment of null allele detection: inconsistencies between and within different methods
title_short Data from: Reliability assessment of null allele detection: inconsistencies between and within different methods
title_full Data from: Reliability assessment of null allele detection: inconsistencies between and within different methods
title_fullStr Data from: Reliability assessment of null allele detection: inconsistencies between and within different methods
title_full_unstemmed Data from: Reliability assessment of null allele detection: inconsistencies between and within different methods
title_sort data from: reliability assessment of null allele detection: inconsistencies between and within different methods
publisher Zenodo
publishDate 2013
url https://doi.org/10.5061/dryad.4p41m
genre Tundra
genre_facet Tundra
op_relation https://doi.org/10.1111/1755-0998.12177
https://zenodo.org/communities/dryad
https://doi.org/10.5061/dryad.4p41m
oai:zenodo.org:4998761
op_rights info:eu-repo/semantics/openAccess
Creative Commons Zero v1.0 Universal
https://creativecommons.org/publicdomain/zero/1.0/legalcode
op_doi https://doi.org/10.5061/dryad.4p41m10.1111/1755-0998.12177
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