Data from: A global assembly of landrace oat (<i>Avena sativa</i> L.) accessions is a discovery resource for adaptive variation, association mapping, and trait deployment
Oat Landrace Diversity (OLD) Panel phenotypes, genotypes, and metadata from: Rahman et al. (2024) "A global assembly of landrace oat (Avena sativa L.) accessions is a discovery resource for adaptive variation, association mapping, and trait deployment".
"File S1" and "File S2" include population metadata and phenotypic (environmental) data used in association mapping, of which mapping results are listed in "File S3".
"Rahman_et_al_2024_Metadata.geojson" is geographical information of OLD Panel accessions surveyed in this study.
"SBATCH_RUN_nsgc_deepvariant_glsnexus.sh" and "RUN_nsgc_deepvariant_glsnexus.sh" are scripts for variant calling and filtering in SciNet clusters from GBS alignments. IMPORTANT: Do not pull containers in $HOME directory - put them in the main path (for use in SciNet clusters). Google DeepVariant - generates "deepvariant_1.6.0.sif" (RUN: singularity pull docker://google/deepvariant:1.6.0); GLNexus - generates "glnexus_v1.4.1.sif" (RUN: singularity pull docker://google/glnexus:1.4.1). "DeepVariantWGS.yml" is the config file for running GLNexus.
"nsgc.gdv.gln.cohort.clean.maf01maxmiss75diploid.beagle_sorted_filt.gt.vcf" is the final genotype file described in the study.
Resources
9 resources available
-
Geodata ISO 19139 metadata
XML -
File S1.xlsx
XLSX -
nsgc.gdv.gln.cohort.clean.maf01maxmiss75diploid.beagle_sorted_filt.gt.vcf
VCF -
File S2.xlsx
XLSX -
Rahman_et_al_2024_Metadata.geojson
GEOJSON -
File S3.xlsx
XLSX -
SBATCH_RUN_nsgc_deepvariant_glsnexus.sh
SH -
RUN_nsgc_deepvariant_glsnexus.sh
SH -
DeepVariantWGS.yml
YML
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Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| bureauCode |
[ "005:18" ] |
| contactPoint |
{ "fn": "Carlson, Craig, H.", "hasEmail": "mailto:craig.h.carlson@usda.gov" } |
| description | <p>Oat Landrace Diversity (OLD) Panel phenotypes, genotypes, and metadata from: Rahman et al. (2024) "A global assembly of landrace oat (<em>Avena sativa</em> L.) accessions is a discovery resource for adaptive variation, association mapping, and trait deployment".</p> <p><strong>"File S1"</strong> and <strong>"File S2"</strong> include population metadata and phenotypic (environmental) data used in association mapping, of which mapping results are listed in <strong>"File S3"</strong>.</p> <p><strong>"Rahman_et_al_2024_Metadata.geojson"</strong> is geographical information of OLD Panel accessions surveyed in this study.</p> <p><strong>"SBATCH_RUN_nsgc_deepvariant_glsnexus.sh"</strong> and <strong>"RUN_nsgc_deepvariant_glsnexus.sh"</strong> are scripts for variant calling and filtering in SciNet clusters from GBS alignments. IMPORTANT: Do not pull containers in $HOME directory - put them in the main path (for use in SciNet clusters). Google DeepVariant - generates "deepvariant_1.6.0.sif" (RUN: singularity pull docker://google/deepvariant:1.6.0); GLNexus - generates "glnexus_v1.4.1.sif" (RUN: singularity pull docker://google/glnexus:1.4.1). <strong>"DeepVariantWGS.yml"</strong> is the config file for running GLNexus.</p> <p><strong>"nsgc.gdv.gln.cohort.clean.maf01maxmiss75diploid.beagle_sorted_filt.gt.vcf"</strong> is the final genotype file described in the study.</p> |
| distribution |
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| identifier | 10.15482/USDA.ADC/27095383.v1 |
| keyword |
[ "Adaptation", "Climate change", "Founder population", "Functional traits", "GWAS", "Landrace", "Oats", "QTL" ] |
| license | https://creativecommons.org/licenses/by/4.0/ |
| modified | 2025-11-21 |
| programCode |
[ "005:040" ] |
| publisher |
{ "name": "Agricultural Research Service", "@type": "org:Organization" } |
| spatial |
"{"type": "Polygon", "coordinates": [[[-153.0, -42.65], [174.88571, -42.65], [174.88571, 65.0], [-153.0, 65.0], [-153.0, -42.65]]]}"
|
| temporal | 2024-09-24/2024-09-24 |
| theme |
[ "geospatial" ] |
| title | Data from: A global assembly of landrace oat (<i>Avena sativa</i> L.) accessions is a discovery resource for adaptive variation, association mapping, and trait deployment |
