Simupop_code.tar.gz

This archive contains Python code for simulating populations using the package simuPOP, plus additional data files, used in Pritchard et al. (2016): *.py: code for simulating test or reference individuals. Estimated_allele_frequencies.csv: estimated frequencies of the 200 discriminatory alleles, fro...

Full description

Bibliographic Details
Main Authors: Pritchard, Victoria L., Erkinaro, Jaakko, Kent, Matthew P., Niemelä, Eero, Orell, Panu, Lien, Sigbjørn, Primmer, Craig R.
Format: Dataset
Language:unknown
Published: Dryad Digital Repository 2016
Subjects:
Online Access:https://dx.doi.org/10.5061/dryad.dg8f3/3
http://datadryad.org/resource/doi:10.5061/dryad.dg8f3/3
id ftdatacite:10.5061/dryad.dg8f3/3
record_format openpolar
spelling ftdatacite:10.5061/dryad.dg8f3/3 2023-05-15T15:31:01+02:00 Simupop_code.tar.gz Pritchard, Victoria L. Erkinaro, Jaakko Kent, Matthew P. Niemelä, Eero Orell, Panu Lien, Sigbjørn Primmer, Craig R. 2016 https://dx.doi.org/10.5061/dryad.dg8f3/3 http://datadryad.org/resource/doi:10.5061/dryad.dg8f3/3 unknown Dryad Digital Repository https://dx.doi.org/10.5061/dryad.dg8f3 http://creativecommons.org/publicdomain/zero/1.0 CC0 Atlantic salmon aquaculture escapee introgressive hybridization SNP array allelotyping North Atlantic Holocene Salmo salar dataset Dataset DataFile 2016 ftdatacite https://doi.org/10.5061/dryad.dg8f3/3 https://doi.org/10.5061/dryad.dg8f3 2021-11-05T12:55:41Z This archive contains Python code for simulating populations using the package simuPOP, plus additional data files, used in Pritchard et al. (2016): *.py: code for simulating test or reference individuals. Estimated_allele_frequencies.csv: estimated frequencies of the 200 discriminatory alleles, from Table S3. Allele_frequencies_for_simulations.csv: adjusted allele frequencies used for simulations, from Table S3. See README file in archive for further information. Dataset Atlantic salmon North Atlantic Salmo salar DataCite Metadata Store (German National Library of Science and Technology)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic Atlantic salmon
aquaculture escapee
introgressive hybridization
SNP array
allelotyping
North Atlantic
Holocene
Salmo salar
spellingShingle Atlantic salmon
aquaculture escapee
introgressive hybridization
SNP array
allelotyping
North Atlantic
Holocene
Salmo salar
Pritchard, Victoria L.
Erkinaro, Jaakko
Kent, Matthew P.
Niemelä, Eero
Orell, Panu
Lien, Sigbjørn
Primmer, Craig R.
Simupop_code.tar.gz
topic_facet Atlantic salmon
aquaculture escapee
introgressive hybridization
SNP array
allelotyping
North Atlantic
Holocene
Salmo salar
description This archive contains Python code for simulating populations using the package simuPOP, plus additional data files, used in Pritchard et al. (2016): *.py: code for simulating test or reference individuals. Estimated_allele_frequencies.csv: estimated frequencies of the 200 discriminatory alleles, from Table S3. Allele_frequencies_for_simulations.csv: adjusted allele frequencies used for simulations, from Table S3. See README file in archive for further information.
format Dataset
author Pritchard, Victoria L.
Erkinaro, Jaakko
Kent, Matthew P.
Niemelä, Eero
Orell, Panu
Lien, Sigbjørn
Primmer, Craig R.
author_facet Pritchard, Victoria L.
Erkinaro, Jaakko
Kent, Matthew P.
Niemelä, Eero
Orell, Panu
Lien, Sigbjørn
Primmer, Craig R.
author_sort Pritchard, Victoria L.
title Simupop_code.tar.gz
title_short Simupop_code.tar.gz
title_full Simupop_code.tar.gz
title_fullStr Simupop_code.tar.gz
title_full_unstemmed Simupop_code.tar.gz
title_sort simupop_code.tar.gz
publisher Dryad Digital Repository
publishDate 2016
url https://dx.doi.org/10.5061/dryad.dg8f3/3
http://datadryad.org/resource/doi:10.5061/dryad.dg8f3/3
genre Atlantic salmon
North Atlantic
Salmo salar
genre_facet Atlantic salmon
North Atlantic
Salmo salar
op_relation https://dx.doi.org/10.5061/dryad.dg8f3
op_rights http://creativecommons.org/publicdomain/zero/1.0
op_rightsnorm CC0
op_doi https://doi.org/10.5061/dryad.dg8f3/3
https://doi.org/10.5061/dryad.dg8f3
_version_ 1766361513434546176