Dataset	Reference Genome	Accessions	Variant Sites	Key Filters	Heterozygous Sites	SNPs	InDels	Paper	Notes
Wild Barley SNPs (High Quality)	Morex v3	281	985,241	Mapping quality (≥ 30), Genotypic coverage (≥ 50%), LD (max R² > 0.5)	✔	✔	✘	Spanner R, et al. (2025)	See the Help and Download tabs for more information about the dataset.
Wild Barley SNPs (High Coverage)	Morex v3	281	212,521,313	Mapping quality (≥ 30), Genotypic coverage (≥ 50%)	✔	✔	✘	Spanner R, et al. (2025)	See the Help and Download tabs for more information about the dataset.
Wild Barley InDels (High Quality)	Morex v3	281	2,675,250	Mapping quality (≥ 30), Genotypic coverage (≥ 50%), LD (max R² > 0.5)	✔	✘	✔	Spanner R, et al. (2025)	See the Help and Download tabs for more information about the dataset.
Wild Barley InDels (High Coverage)	Morex v3	281	13,847,535	Mapping quality (≥ 30), Genotypic coverage (≥ 50%), LD (max R² > 0.5)	✔	✘	✔	Spanner R, et al. (2025)	See the Help and Download tabs for more information about the dataset.

SNPversity 2.0 Data Downloads

Release 2.0.80 (20 September 2024)

Overview

Below you will find detailed information about the datasets available for download, along with guidelines and best practices. For more information on how the datasets were generated see the 'Help' section.

How to Download

Raw SNPs (FigShare): Original raw SNP VCF files are here with a permanent DOI (10.6084/m9.figshare.30531372).
Passport data: Passport data for each wild barley sample avialble in the supplementary data here.
GitHub: GitHub repository with the code used for variant calling available here.
High-coverage SNP VCFs (GrainGenes): Files were processed using the SNPversity workflow and are available here.
High-quality SNP VCFs (GrainGenes): Files were processed using the SNPversity workflow and are available here.
High-coverage InDel VCFs (GrainGenes): Files were processed using the SNPversity workflow and are available here.
High-quality SNP VCFs (GrainGenes): Files were processed using the SNPversity workflow and are available here.

Download Instructions

Prepare Adequate Storage: Ensure you have sufficient storage space on your system for the download.
Use a Reliable Internet Connection: A wired connection is recommended for faster and more stable downloads.
Consider Using a Download Manager: For large files, a download manager can help manage the download process, allowing for pause, resume, and recovery of the download.
Verify Data Integrity: After download, use checksums (provided in the tables below) to verify the integrity of the downloaded files.

Barley High Coverage SNP Datasets (VCFs) Download

Dataset Name	Description	Size	MD5 Checksum
chr1H.high_coverage.vcf.gz	High Coverage SNP variants and metadata identified in Chromsome 1H	1.18 GB	46c46a25a88541a4961cfe9d4e25104b
chr2H.high_coverage.vcf.gz	High Coverage SNP variants and metadata identified in Chromsome 2H	1.55 GB	b1ccb1a3f124dc34c87c85ec81aa207f
chr3H.high_coverage.vcf.gz	High Coverage SNP variants and metadata identified in Chromsome 3H	1.48 GB	9540b9de8cba3d5c43047fe9ff539ce9
chr4H.high_coverage.vcf.gz	High Coverage SNP variants and metadata identified in Chromsome 4H	1.47 GB	6c7b8eed0120e420f25bc7881d6c0149
chr5H.high_coverage.vcf.gz	High Coverage SNP variants and metadata identified in Chromsome 5H	1.32 GB	4414107070a511c46c784939383cabdf
chr6H.high_coverage.vcf.gz	High Coverage SNP variants and metadata identified in Chromsome 6H	1.31 GB	b1305985578042bdda0209e40339474c
chr7H.high_coverage.vcf.gz	High Coverage SNP variants and metadata identified in Chromsome 7H	1.51 GB	720dcca043983ff330dbbd8682f8a4b5

Barley High Quality SNP Datasets (VCFs) Download

Dataset Name	Description	Size	MD5 Checksum
chr1H.high_quality.vcf.gz	High Quality SNP variants identified in Chromsome 1H	11 MB	ff1d939804560c961397f3351499fdfe
chr2H.high_quality.vcf.gz	High Quality SNP variants identified in Chromsome 2H	14 MB	dc3ae1695f96029de98098e50443f4c5
chr3H.high_quality.vcf.gz	High Quality SNP variants identified in Chromsome 3H	15 MB	fabe5a9a58ac1c482fd668ad9395e6cd
chr4H.high_quality.vcf.gz	High Quality SNP variants identified in Chromsome 4H	5 MB	0962f1e32ab40cd2f87b1481a90d1f25
chr5H.high_quality.vcf.gz	High Quality SNP variants identified in Chromsome 5H	14 MB	fcf674464fdc78a53d557f0a2f3748f9
chr6H.high_quality.vcf.gz	High Quality SNP variants identified in Chromsome 6H	11 MB	434d02ea3331edde57d756e0177e90b5
chr7H.high_quality.vcf.gz	High Quality SNP variants identified in Chromsome 7H	15 MB	17309202b24d42e5b20515a18c290f09

Barley High Coverage InDel Datasets (VCFs) Download

Dataset Name	Description	Size	MD5 Checksum
chr1H.high_coverage.vcf.gz	High Coverage InDel variants identified in Chromsome 1H	122 MB	a638e5a6a2e68e3d169b7fcdada79589
chr2H.high_coverage.vcf.gz	High Coverage InDel variants identified in Chromsome 2H	159 MB	c39d1912d6eed9224a64ef8d3be42018
chr3H.high_coverage.vcf.gz	High Coverage InDel variants identified in Chromsome 3H	154 MB	53f745e0dbc0ff99193954e3d7880c28
chr4H.high_coverage.vcf.gz	High Coverage InDel variants identified in Chromsome 4H	143 MB	76d155919bf5eb947aacd7f1551543a5
chr5H.high_coverage.vcf.gz	High Coverage InDel variants identified in Chromsome 5H	139 MB	b2c5076a1d2e63e065c8f52d97ce79a4
chr6H.high_coverage.vcf.gz	High Coverage InDel variants identified in Chromsome 6H	132 MB	7a54684350cec206c3dc366b0fb20fd4
chr7H.high_coverage.vcf.gz	High Coverage InDel variants identified in Chromsome 7H	158 MB	f4a76dd8a8cc10d41b7a8500b86194ca

Barley High Quality InDel Datasets (VCFs) Download

Dataset Name	Description	Size	MD5 Checksum
chr1H.high_quality.vcf.gz	High Quality InDel variants identified in Chromsome 1H	24 MB	be7b270b1ca048bc14c46629dea895ab
chr2H.high_quality.vcf.gz	High Quality InDel variants identified in Chromsome 2H	31 MB	31eda619e2e77c65127dd2112da5b0d9
chr3H.high_quality.vcf.gz	High Quality InDel variants identified in Chromsome 3H	31 MB	d202fb1da546a46ab5f231a572744793
chr4H.high_quality.vcf.gz	High Quality InDel variants identified in Chromsome 4H	29 MB	daf62688bf97841a8f9fc030dbb1f28b
chr5H.high_quality.vcf.gz	High Quality InDel variants identified in Chromsome 5H	28 MB	edc7b9b05994374a03543a8c5047aa43
chr6H.high_quality.vcf.gz	High Quality InDel variants identified in Chromsome 6H	25 MB	cff1dd53c84a829712497b44b5cbd5ab
chr7H.high_quality.vcf.gz	High Quality InDel variants identified in Chromsome 7H	33 MB	83d0cbc5ab0e0b7cf924eaacec3726e5

Need Help?

If you encounter any issues during the download or have any questions, please contact through GrainGenes Feedback.

Disclaimer

We reserve the right to modify the access procedures to ensure data security, integrity, and convenience. This includes using another platform to host the datasets. This page will be updated with the most up-to-date datasets and methods of accessing the data.

SNPversity 2.0

Release 2.0.80 (20 September 2024)

Citation

If you use SNPversity for your research, please cite one or more of the following

SNPversity 2.0
Andorf CM, et al. (2025) A unified VCF dataset from nearly 1,500 diverse maize accessions and resources to explore the genomic landscape of maize. G3 Genes|Genomes|Genetics. doi:10.1093/g3journal/jkae281.
SNPversity
Schott DA, et al. (2025) SNPversity: a web-based tool for visualizing diversity. Database. doi:10.1093/database/bay037.
GrainGenes Database
Yao E, et al. (2025). GrainGenes: genetics, genomes, and pangenomes. Genetics. doi:10.1093/genetics/iyaf270
Wild Barley (Hordeum vulgare ssp. spontaneum) Dataset
Spanner R, et al. (2025). Whole-Genome Resequencing of the Wild Barley Diversity Collection: A Resource for Identifying and Exploiting Genetic Variation for Cultivated Barley Improvement. G3 Genes|Genomes|Genetics. doi:10.1093/g3journal/jkaf261

Overview

Welcome to SNPversity 2.0, the second generation of the SNPversity platform. Designed as an open-source visualization tool, SNPversity 2.0 enables users to explore extensive variant datasets with ease. Here's how it works:

Input & Output: Users can input specific genomic intervals and select accessions of interest. SNPversity 2.0 processes this input to deliver a Variant Call Format (VCF) file and a detailed table. These outputs showcase the alleles matching the user's query, providing a clear and concise visualization of genetic variations.
Technical Architecture: At its core, SNPversity 2.0 is powered by a robust HDF5 database back-end that manages variant annotations efficiently. A data exchange layer, developed in Python, facilitates seamless data handling, while a JavaScript-based interface layer presents Single Nucleotide Polymorphisms (SNPs) and Insertions/Deletions (InDels) in an interactive format.
Real-Time Visualization: SNPversity 2.0 elevates data presentation by displaying information in real-time directly in your web browser. Tables are intuitively color-coded, reflecting each SNP's allelic status and mutational state for straightforward interpretation.
Enhanced Data Insights: Beyond basic variant data, SNPversity 2.0 enriches your research with valuable metadata. This includes variant effect annotations, mapping quality scores, genotypic coverage, and maximum R2 scores to indicate linkage disequilibrium, offering a comprehensive view of genetic variations.

Code

For information about the code used in SNPversity 2.0 please refer to the GitHub page. This page provides detailed information about web compatibility, the directory structure, system requirements, and a comprehensive description of the code. It also offers guidance on how to use the websites, information about the pipelines used, and instructions on preparing data for PanEffect.

For more details, please visit our GitHub page: GitHub - SNPversity 2.0.

How to use the website

There are four tabs in the SNPversity 2.0 website 'Select options', 'Table view', 'Tree view', and 'Help'.

Select options

The two main inputs for this tool are selecting the genomic interval of interest and which subset of accessions to include.

Select genomic interval:
This section allows the user to select the genomic interval of interest. The two main options are entering the genomic coordinates or entering a gene model identifier.

Genome Version: Select the reference genome version. The only option currently available is barley Morex version 3.
Dataset: Select the variation dataset to query. The 'High Quality' datasets were filtered on mapping quality (>= 30), genotypic coverage (>= 50%), and linkage disequilibrium with max R2 > 0.5. The 'High Coverage' datasets were filtered only on mapping quality (>= 30) and genotypic coverage (>= 50%).
Chromosome: Select the chromosome.
Genome Start Position (bp): Select the start position on the chromosome.
Genome End Position (bp): Select the end position on the chromosome.
Loci per page: Select the number of loci to view per page in the HTML table view. This number corresponds to the number of rows in the table.
Gene Model ID: Optionally, select the gene model identifier and the number of base pairs to add as padding to the start and end of the gene model coordinates. Pressing the 'Load coordinates' button will load the chromosome, start, and end positions if the gene model is found. This option currently only accepts barley Morex (v3) gene models.

(NOTE: Genomic regions larger than 1 MB will only be avaialble as VCF downloads. The table and tree views will not be available.)

Select which accessions to include:
This section allows the user to select a subset of the accessions to view. The two main options are to upload a file with the accession IDs, use the buttons to randomly subsample the datasets, or use the checkboxes to manually select the accessions. A list of all accessions can be found in XLSX.

Table view

The table view option allows the user to download the VCF generated from the select options tab and displays a table of the data (for regions <= 1Mb). Each row of the data corresponds to a locus position in the dataset. The descriptions of the columns are in the following table.

Column name	Definition	Abbreviation	Example data
Chromosome	CHR	The chromosome where the locus is located	chr1
Position	POS	The genomic coordinate on the chromosome	104985
Reference allele	REF	The allele value for the locus in the reference genome barley Morex (v3).	A
Alternate allele	ALT	The alternative allele value found in other maize accessions	T
Gene models	Gene model(s)	The name of the barley Morex (v3) gene model affected by the variant. Displays the closest gene models when the variant is intergenic.	HORVU.MOREX.r3.1HG0090290
Effect type	Effect type	The type of effect using Sequence Ontology terms.	stop gained
Effect impact	Effect impact	A estimation of putative impact/deleteriousness.	HIGH MODIFIER
Mapping quality score	MQ	The average mapping quality of reads supporting the variant.	58
Completeness	COMP	The percent of accessions that provide genotype data for a particular variant (i.e., there is at least one read for that accession at the given variant). Note, this is different than read coverage	99
Maximum squared correlation	max R2	The linkage disequilibrium measured by the maximum R2 for a given loci.	0.64
Minor allele frequency	MAF	Minor Allele Frequency (MAF) is the proportion of the less common allele at a genetic locus within a given population.	0.23

The gene models in the Gene model(s) column are linked to the GrainGenes barley Morex (v3) genome browser. The position of the locus is shown as a vertical line on the browser.

Variant effects were calculated using SNPeff.

Linkage disequilibrium values were calculated using Plink.

The remainder of the columns are based on the subset of selected barley accessions. There is one column for each barley accession and the column header is color-coded based on the project. The columns are named based on the accession name, an underscore, and the SRR ID. The values and colors of the data in these columns are based on the allele value for the given locus for that accession.

0 Homozygous reference genotype
1 Heterozygous genotype with one reference and one alternate allele
2 Homozygous alternate genotype
N Missing or unknown genotypes

Variant effect types

VCF Column	Description
MQ	Mapping quality score - The average mapping quality of reads supporting the variant
COMP	Completeness - The percent of accessions that provide genotype data for a particular variant
max R2	Maximum squared correlation - The linkage disequilibrium measured by the maximum R2 for a given loci
MAF	Minor allele frequency - The proportion of the less common allele at a genetic locus within a given population

Seq. Ontology	Effect	Description	Impact
intergenic_region	INTERGENIC	The variant is in an intergenic region	MODIFIER
upstream_gene_variant	UPSTREAM	Upstream of a gene (default length: 5K bases)	MODIFIER
5_prime_UTR_variant	UTR_5_PRIME	Variant hits 5'UTR region	MODIFIER
coding_sequence_variant	CDS	The variant hits a CDS.	MODIFIER
exon_variant	EXON	The variant hits an exon (from a non-coding transcript) or a retained intron.	MODIFIER
intron_variant	INTRON	Variant hits an intron. Technically, hits no exon in the transcript.	MODIFIER
frameshift_variant	FRAME_SHIFT	Insertion or deletion causes a frame shift e.g.: An indel size is not multiple of 3	HIGH
missense_variant	NON_SYNONYMOUS_CODING	Variant causes a codon that produces a different amino acid e.g.: Tgg/Cgg, W/R	MODERATE
synonymous_variant	SYNONYMOUS_CODING	Variant causes a codon that produces the same amino acid e.g.: Ttg/Ctg, L/L	LOW
stop_lost	STOP_LOST	Variant causes stop codon to be mutated into a non-stop codon e.g.: Tga/Cga, */R	HIGH
stop_gained	STOP_GAINED	Variant causes a STOP codon e.g.: Cag/Tag, Q/*	HIGH
3_prime_UTR_variant	UTR_3_PRIME	Variant hits 3'UTR region	MODIFIER
downstream_gene_variant	DOWNSTREAM	Downstream of a gene (default length: 5K bases)	MODIFIER

Impact	Meaning	Example
HIGH	The variant is assumed to have high (disruptive) impact in the protein, probably causing protein truncation, loss of function or triggering nonsense mediated decay.	stop_gained, frameshift_variant
MODERATE	A non-disruptive variant that might change protein effectiveness.	missense_variant, inframe_deletion
LOW	Assumed to be mostly harmless or unlikely to change protein behavior.	synonymous_variant
MODIFIER	Usually non-coding variants or variants affecting non-coding genes, where predictions are difficult or there is no evidence of impact.	exon_variant, downstream_gene_variant

To see a full list of the variant effect types click here.

VCF Download from Search

After completing a search based on a genomic region and a subset of accessions, a "Download the VCF file" button will be available in the "Table view" tab. When the user clicks this link, a subset of the variants meeting the search criteria will be downloaded as a VCF file. The VCF will only include the specified set of accessions and each variant within the selected genomic region. The VCF will contain rows with no variant relative to the reference. The genotype coverage fields (CVC and CVP) will refer to the number of accessions with genotype data for a particular variant based on all 1,525 accessions, not the local genotype coverage of the selected accessions.

Below is a sample of an output VCF file generated from SNPversity 2.0:

##fileformat=VCFv4.2
##fileDate=20240531
##source=MaizeGDB2024
##INFO=<ID=MQ,Number=1,Type=Float,Description="RMS mapping quality">
##INFO=<ID=CVC,Number=1,Type=Integer,Description="The number of accessions that have genotype data for a particular variant">
##INFO=<ID=CVP,Number=1,Type=Float,Description="The percent of accessions that have genotype data for a particular variant.">
##INFO=<ID=TYPE,Number=.,Type=String,Description="The type of effect using Sequence Ontology terms">
##INFO=<ID=EFFECT,Number=.,Type=String,Description="An estimation of putative impact/deleteriousness">
##INFO=<ID=GENEMODEL,Number=.,Type=String,Description="The name of the gene model affected by the variant">
##INFO=<ID=SUB,Number=.,Type=String,Description="The amino acid substitution for missense and non-synonymous variants">
##INFO=<ID=MAXR2,Number=1,Type=Float,Description="The maximum R2 for a given loci">
##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype">
#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	CML228_SRR8906784	CML69_SRR8906963	B97_CRX445264	CML322_CRX445267	CML333_CRX445268	CML52_SRR5725841	CML103_SRR5976229	M37W_SRR5976317
chr10	218441	.	T	C	5127.59	.	MQ=59.89;CVC=1481;CVP=98.87;TYPE=3_prime_UTR_variant;EFFECT=MODIFIER;GENEMODEL=Zm00001eb404760;SUB=NA;MAXR2=0.910833	GT	0/0	1/1	0/0	0/0	0/0	0/0	0/0	0/0
chr10	218443	.	G	A	5127.84	.	MQ=60;CVC=1484;CVP=99.07;TYPE=3_prime_UTR_variant;EFFECT=MODIFIER;GENEMODEL=Zm00001eb404760;SUB=NA;MAXR2=0.910835	GT	0/0	1/1	0/0	0/0	0/0	0/0	0/0	0/0
chr10	218458	.	T	C	1656.67	.	MQ=53.05;CVC=1484;CVP=99.07;TYPE=3_prime_UTR_variant;EFFECT=MODIFIER;GENEMODEL=Zm00001eb404760;SUB=NA;MAXR2=0.666034	GT	0/0	0/0	0/0	0/0	0/0	0/0	0/0	0/0
chr10	218498	.	T	A	1715.17	.	MQ=52.05;CVC=1465;CVP=97.80;TYPE=3_prime_UTR_variant;EFFECT=MODIFIER;GENEMODEL=Zm00001eb404760;SUB=NA;MAXR2=0.916933	GT	0/0	1/1	0/0	0/0	0/0	0/0	0/0	0/0
chr10	218502	.	C	CTCTGTCTG	1676.75	.	MQ=47.9;CVC=1444;CVP=96.40;TYPE=3_prime_UTR_variant;EFFECT=MODIFIER;GENEMODEL=Zm00001eb404760;SUB=NA;MAXR2=0.916923	GT	0/0	1/1	0/0	0/0	0/0	0/0	0/0	0/0

Tree view

The tree view option allows the user to generate phylogenetic tree views based on the VCF2PopTree tool. The input to build the tree is based on the VCF file generated from the select options tab.

The tree tree can be constructed as either an UPGMA tree or Neighbour-Joining tree (Unrooted). The drawing options are inlcudes Rectangular tree or Radial tree. In addtion, the trees can be saved in the following text formats: Newick tree, Pair-wise diversity (MEGA), or PHYLIP.

Downloads

The Downloads tab provides detailed information about the datasets available for download, along with guidelines and best practices.

Help

The help page gives an overview of the webpage, descriptions of the datasets and methods, and how to use the website.

Chromosome:
Genome Start Position (bp):
Genome End Position (bp):
Loci per page:

WBDC001	WBDC002	WBDC004	WBDC005	WBDC006	WBDC007
WBDC008	WBDC009	WBDC010	WBDC011	WBDC012	WBDC013
WBDC014	WBDC015	WBDC016	WBDC017	WBDC018	WBDC019
WBDC020	WBDC021	WBDC022	WBDC023	WBDC024	WBDC025
WBDC026	WBDC028	WBDC029	WBDC030	WBDC031	WBDC032
WBDC033	WBDC034	WBDC035	WBDC036	WBDC038	WBDC040
WBDC041	WBDC042	WBDC043	WBDC044	WBDC045	WBDC046
WBDC049	WBDC051	WBDC052	WBDC053	WBDC054	WBDC055
WBDC056	WBDC057	WBDC058	WBDC060	WBDC061	WBDC062
WBDC063	WBDC064	WBDC066	WBDC067	WBDC068	WBDC070
WBDC072	WBDC073	WBDC074	WBDC075	WBDC078	WBDC079
WBDC080	WBDC082	WBDC083	WBDC085	WBDC089	WBDC092
WBDC093	WBDC094	WBDC095	WBDC097	WBDC100	WBDC101
WBDC104	WBDC105	WBDC106	WBDC107	WBDC108	WBDC109
WBDC110	WBDC111	WBDC112	WBDC113	WBDC115	WBDC116
WBDC117	WBDC119	WBDC120	WBDC121	WBDC122	WBDC123
WBDC125	WBDC126	WBDC127	WBDC128	WBDC129	WBDC130
WBDC133	WBDC134	WBDC136	WBDC137	WBDC138	WBDC139
WBDC140	WBDC142	WBDC143	WBDC145	WBDC146	WBDC147
WBDC148	WBDC149	WBDC150	WBDC151	WBDC152	WBDC153
WBDC155	WBDC156	WBDC157	WBDC159	WBDC160	WBDC161
WBDC164	WBDC165	WBDC167	WBDC168	WBDC169	WBDC170
WBDC171	WBDC172	WBDC173	WBDC174	WBDC175	WBDC177
WBDC178	WBDC179	WBDC180	WBDC181	WBDC182	WBDC183
WBDC184	WBDC185	WBDC186	WBDC187	WBDC188	WBDC189
WBDC190	WBDC191	WBDC192	WBDC193	WBDC194	WBDC195
WBDC196	WBDC197	WBDC198	WBDC199	WBDC200	WBDC201
WBDC202	WBDC203	WBDC204	WBDC205	WBDC206	WBDC207
WBDC208	WBDC209	WBDC210	WBDC211	WBDC212	WBDC213
WBDC214	WBDC215	WBDC216	WBDC217	WBDC219	WBDC220
WBDC221	WBDC223	WBDC224	WBDC228	WBDC231	WBDC232
WBDC233	WBDC234	WBDC236	WBDC237	WBDC238	WBDC241
WBDC242	WBDC243	WBDC244	WBDC245	WBDC246	WBDC247
WBDC248	WBDC250	WBDC252	WBDC253	WBDC254	WBDC255
WBDC256	WBDC257	WBDC258	WBDC260	WBDC265	WBDC266
WBDC267	WBDC268	WBDC269	WBDC270	WBDC271	WBDC274
WBDC275	WBDC276	WBDC277	WBDC278	WBDC279	WBDC281
WBDC282	WBDC283	WBDC284	WBDC285	WBDC286	WBDC287
WBDC289	WBDC290	WBDC291	WBDC292	WBDC293	WBDC294
WBDC295	WBDC296	WBDC297	WBDC298	WBDC299	WBDC300
WBDC302	WBDC303	WBDC304	WBDC305	WBDC306	WBDC307
WBDC308	WBDC309	WBDC311	WBDC312	WBDC314	WBDC315
WBDC317	WBDC318	WBDC319	WBDC320	WBDC323	WBDC324
WBDC326	WBDC329	WBDC330	WBDC331	WBDC332	WBDC333
WBDC335	WBDC336	WBDC337	WBDC338	WBDC340	WBDC341
WBDC342	WBDC343	WBDC344	WBDC345	WBDC346	WBDC347
WBDC348	WBDC349	WBDC350	WBDC354	WBDC355

Construct Tree	UPGMA tree Neighbour-Joining tree (Unrooted)
Drawing options	Rectangular tree Radial tree
Output format	Newick tree Pair-wise diversity (MEGA) PHYLIP

Accessions	Project	Project name	Color Key
27	PRJEB31061	Genome sequence and assembly of the 25 founder lines of the the NAM population.
539	PRJCA009749	WGS resequencing of 1,604 maize inbred lines
519	PRJNA531553	Deep DNA resequencing of the association mapping panel
340	PRJNA783885	Maize landrace whole genome resequencing
35	PRJEB56320	Maize Wisconsin Diversity Panel Resequencing
32	PRJNA609577	Zea mays Genome sequencing
11	PRJNA389800	Whole genome sequencing of maize 282 panel
8	PRJEB14212	European maize diversity
7	PRJNA399729	Maize Haplotype Map version 3
6	PRJNA260788	Zea mays Genome sequencing (European maize genomes)
1	PRJEB56265	Resequencing of three Polish maize inbred lines

Accessions	Project	Project name	Color Key
58	PRJEB14212	European maize diversity [2017].
214	PRJNA399729	Maize Haplotype Map version 3 [2017]
224	PRJNA641489 PRJNA816255 PRJNA816273 PRJNA645739	Genetics diversity of Zea [2022]
48	PRJNA479960	South American maize genome sequencing [2018]
473	PRJNA661271	Maize Wisconsin Diversity Panel Resequencing Project [2021]
239	PRJEB56265 PRJEB56295 PRJEB56320	Resequencing of three Polish maize inbred lines & Maize Wisconsin Diversity Panel [2023]
26	PRJNA260788	Zea mays Genome sequencing [2014]
35	PRJNA300309	Zea mays subsp. mays (maize) with Z. parviglumis [2017]
198	PRJNA609577	Zea mays Genome sequencing [2020]

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