About variant identifiers


All of the 1000 Genomes SNPs and indels have been submitted to dbSNP, and will have rsIDs in the main 1000 Genomes release files. The SVs have all been submitted to DGVa and have esvIDs in the main files.

If you are using some of the older working files that were used during the data gathering phase of the 1000 Genomes Project, you may find some variants with other kinds of identifiers, such as Alu_umary_Alu_###. These identifiers were created internally by the groups that did that set of particular variant calling, and are not found anywhere other than these files, as they will have been replaced by official IDs in the later files.

KGP identifiers

You may also see kgp identifiers, which were created by Illumina for their genotyping platform before some variants identified during the pilot phase of the project had been assigned rs numbers.

We do not possess a mapping of these identifiers to current rs numbers. As far as we are aware no such list exists.

Related questions:

About VCF variant files


Variants are released in VCF format. As these have been released at different times, they are on different versions of the format - this will be indicated in the file heading. Our VCFs are multi-individual, with genotypes listed for each sample; we do not have individual or population specific VCFs.

Are all the genotype calls in the 1000 Genomes Project VCF files bi-allelic?

No. While bi-allelic calling was used in earlier phases of the 1000 Genomes Project, multi-allelic SNPs, indels, and a diverse set of structural variants (SVs) were called in the final phase 3 call set. More information can be found in the main phase 3 publication from the 1000 Genomes Project and the structural variation publication. The supplementary information for both papers provides further detail.

In earlier phases of the 1000 Genomes Project, the programs used for genotyping were unable to genotype sites with more than two alleles. In most cases, the highest frequency alternative allele was chosen and genotyped. Depth of coverage, base quality and mapping quality were also used when making this decision. This was the approach used in phase 1 of the 1000 Genomes Project. As methods were developed during the 1000 Genomes Project, it is recommended to use the final phase 3 data in preference to earlier call sets.

Related questions:

Are the variant calls in IGSR phased?


You can tell when a VCF file contains a phased genotype as the delimiter used in the GT field is a pipe symbol | e.g

#CHROM  POS     ID      REF     ALT     QUAL    FILTER  INFO    FORMAT  HG00096
10   60523  rs148087467    T     G       100     PASS    AC=0;AF=0.01;AFR_AF=0.06;AMR_AF=0.0028;AN=2; GT:GL 0|0:-0.19,-0.46,-2.28

The VCF files produced by the final phase of the 1000 Genomes Project (phase 3) are phased. They can be found in the final release directory from the project and in the directory supporting the final publications.

Some other studies have also produced phased versions of their calls. These include the analysis of high-coverage data across 3,202 samples on GRCh38 completed by NYGC. Multiple sets of VCFs are available, including phased VCFs, linked to from the page for that collection.

Related questions:

Can I convert VCF files to PLINK/PED format?


We provide a VCF to PED tool to convert from VCF to PLINK PED format. This tool has documentation for both the web interface and the Perl script.

An example Perl command to run the script would be:

perl vcf_to_ped_converter.pl -vcf ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/release/20110521/ALL.chr13.phase1_integrated_calls.20101123.snps_indels_svs.genotypes.vcf.gz
    -sample_panel_file ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/release/20110521/phase1_integrated_calls.20101123.ALL.sample_panel
    -region 13:32889611-32973805 -population GBR -population FIN

Related questions:

Can I get phased genotypes and haplotypes for the individual genomes?


Phased variant call sets are described in “Are the variant calls in IGSR phased?”.

You can obtain individual phased genotypes through either the Ensembl Data Slicer or using a combination of tabix and VCFtools allows you to sub sample VCF files for a particular individual or list of individuals.

The Data Slicer has both filter by individual and population options. The individual filter takes the individual names in the VCF header and presents them as a list before giving you the final file. If you wish to filter by population, you also must provide a panel file which pairs individuals with populations, again you are presented with a list to select from before being given the final file, both lists can have multiple elements selected.

To use tabix you must also use a VCFtools Perl script called vcf-subset. The command line would look like:

tabix -h ftp://ftp-trace.ncbi.nih.gov/1000genomes/ftp/release/20100804/ALL.2of4intersection.20100804.genotypes.vcf.gz 17:1471000-1472000 | perl vcf-subset -c HG00098 | bgzip -c /tmp/HG00098.20100804.genotypes.vcf.gz

Please also note that some studies, such as the second phase of the Human Genome Structural Variation Consortium (HGSVC), are now producing haplotype resolved asssemblies.

Related questions:

Can I query IGSR programmatically?


Our data is in standard formats like SAM and VCF, which have tools associated with them. To manipulate SAM/BAM files look at SAMtools for a C based toolkit and links to APIs in other languages. To interact with VCF files look at VCFtools which is a set of Perl and C++ code.

Related questions:

Can I use the IGSR data for imputation?


The developers of Beagle, Mach and Impute2 have all created data sets based on the 1000 Genomes data to use for imputation.

Please look at the software’s website to find those files.

Related questions:

Do you have structural variation data?


The 1000 Genomes Project considered structural variation (longer than 50bp in length) based on short read Illumina data in the publication by Sudmant et al. in 2015.

Structural variants are also considred in analysis of high-coverage short read data in work done by NYGC.

However, short read data has limitations for assessing structural variation. The Human Genome Structural Variation Consortium (HGSVC) applied a variety of technologies to explore their abilty to detect structural variation. This work has subsequently been expanded and other projects are using a variety of technologies to produce haplotype resolved genome assemblies.

Related questions:

How are allele frequencies calculated?


Our standard AF values are allele frequencies rounded to two decimal places calculated using allele count (AC) and allele number (AN) values.

LDAF is an allele frequency value in the info column of our phase 1 VCF files. LDAF is the allele frequency as inferred from the haplotype estimation. You will note that LDAF does sometimes differ from the AF calculated on the basis of allele count and allele number. This generally means there are many uncertain genotypes for this site. This is particularly true close to the ends of the chromosomes.

Genotype Dosage

The phase 1 data set also contains Genotype Dosage values. This comes from Mach/Thunder, imputation engine used for genotype refinement in the phase 1 data set.

The Dosage represents the predicted dosage of the non reference allele given the data available, it will always have a value between 0 and 2.

The formula is Dosage = Pr(Het|Data) + 2*Pr(Alt|Data)

The dosage value gives an indication of how well the genotype is supported by the imputation engine. The genotype likelihood gives an indication of how well the genotype is supported by the sequence data.

Related questions:

How do I find out information about a single variant?


Our VCF files contain global and super population alternative allele frequencies. You can see this in our most recent release. For multi allelic variants, each alternative allele frequency is presented in a comma separated list.

An example info column which contains this information looks like

1 15211 rs78601809 T G 100 PASS AC=3050;AF=0.609026;AN=5008;NS=2504;DP=32245;EAS_AF=0.504;AMR_AF=0.6772;AFR_AF=0.5371;EUR_AF=0.7316;SAS_AF=0.6401;AA=t|||;VT=SNP

If you want population specific allele frequencies you have three options: * For a single variant you can look at the population genetics page for a variant in the Ensembl browser. This gives you piecharts and a table for a single site. * For a genomic region you can use our allele frequency calculator tool which gives a set of allele frequencies for selected populations * If you would like sub population allele frequences for a whole file, you are best to use the vcftools command line tool.

This is done using a combination of two vcftools commands called vcf-subset and fill-an-ac

An example command set using files from our phase 1 release would look like

grep CEU integrated_call_samples.20101123.ALL.panel | cut -f1 > CEU.samples.list

vcf-subset -c CEU.samples.list ALL.chr13.integrated_phase1_v3.20101123.snps_indels_svs.genotypes.vcf.gz | fill-an-ac |
    bgzip -c > CEU.chr13.phase1.vcf.gz

Once you have this file you can calculate your frequency by dividing AC (allele count) by AN (allele number).

Please note that some early VCF files from the main project used LD information and other variables to help estimate the allele frequency. This means in these files the AF does not always equal AC/AN. In the phase 1 and phase 3 releases, AC/AN should always match the allele frequency quoted.

Lists of identifiers

You can get information about a list of variant identifiers using Ensembl’s Biomart.

This YouTube video gives a tutorial on how to do it.

The basic steps are:

  1. Select the Ensembl Variation Database
  2. Select the Homo sapiens Short Variants (SNPs and indels excluding flagged variants) dataset
  3. Select the Filters menu from the left hand side
  4. Expand the General Variant Filters section
  5. Check the Filter by Variant Name (e.g. rs123, CM000001) [Max 500 advised] box
  6. Add your list of rs numbers to the box or browse for a file which contains this list
  7. Click on the Results Button in the headline section
  8. This should provide you with a table of results which you can also download in Excel or CSV format

If you would like the coordinates on GRCh38, you should use the main Ensembl site, however if you would like the coordinates on GRCh37, you should use the dedicated GRCh37 site.

Related questions:

How do I get a genomic region sub-section of your files?


You can get a subsection of the VCF or BAM files using the Ensembl Data Slicer tool. This tool gives you a web interface requesting the URL of any VCF file and the genomic location you wish to get a sub-slice for. This tool also works for BAM files. This tool also allows you to filter the file for particular individuals or populations if you also provide a panel file.

You can also subset VCFs using tabix on the command line, e.g.

tabix -h ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/release/20100804/ALL.2of4intersection.20100804.genotypes.vcf.gz 2:39967768-39967768

Specifications for the VCF format, and a C++ and Perl tool set for VCF files can be found at vcftools on sourceforge

Please note that all our VCF files using straight intergers and X/Y for their chromosome names in the Ensembl style rather than using chr1 in the UCSC style. If you request a subsection of a vcf file using a chromosome name in the style chrN as shown below it will not work.

tabix -h ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/release/20100804/ALL.2of4intersection.20100804.genotypes.vcf.gz chr2:39967768-39967768

You can subset alignment files with samtools on the command line, e.g.

samtools view -h ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/phase1/data/HG00154/alignment/HG00154.mapped.ILLUMINA.bwa.GBR.low_coverage.20101123.bam 17:7512445-7513455

Samtools supports streaming files and piping commands together both using local and remote files. You can get more help with samtools from the samtools help mailing list

Related questions:

What are your filename conventions?


Our filename conventions depend on the data format being named. This is described in more detail below.


Our sequence files are distributed in gzipped fastq format

Our files are named with the SRA run accession E?SRR000000.filt.fastq.gz. All the reads in the file also hold this name. The files with _1 and _2 in their names are associated with paired end sequencing runs. If there is also a file with no number it is name this represents the fragments where the other end failed qc. The .filt in the name represents the data in the file has been filtered after retrieval from the archive. This filtering process is described in a README.


Our variant files are distributed in vcf format, a format initially designed for the 1000 Genomes Project which has seen wider community adoption.

The majority of our vcf files are named in the form:


This name starts with the population that the variants were discovered in, if ALL is specifed it means all the individuals available at that date were used. Then the region covered by the call set, this can be a chromosome, wgs (which means the file contains at least all the autosomes) or wex (this represents the whole exome) and a description of how the call set was produced or who produced it, the date matches the sequence and alignment freezes used to generate the variant call set. Next a field which describes what type of variant the file contains, then the analysis group used to generate the variant calls, this should be low coverage, exome or integrated and finally we have either sites or genotypes. A sites file just contains the first eight columns of the vcf format and the genotypes files contain individual genotype data as well.

Release directories should also contain panel files which also describe what individuals the variants have genotypes for and what populations those individuals are from.

Related questions:

What is the coverage depth?


The Phase 1 integrated variant set does not report the depth of coverage for each individual at each site. We instead report genotype likelihoods and dosage. If you would like to see depth of coverage numbers you will need to calculate them directly.

The bedtools suite provides a method to do this.

genomeCoverageBed is a tool which can provide a bed file which specifies coverage for every base in the genome and intersectBed which will provide an intersection between two vcf/bed/bam files.

These commands also require samtools, tabix and vcftools to be installed.

An example set of commands would be:

samtools view -b  ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data/HG01375/alignment/HG01375.mapped.ILLUMINA.bwa.CLM.low_coverage.20120522.bam 2:1,000,000-2,000,000 | genomeCoverageBed -ibam stdin -bg > coverage.bg

This command gives you a bedgraph file of the coverage of the HG01375 bam between 2:1,000,000-2,000,000:

tabix -h http://ftp.1000genomes.ebi.ac.uk/vol1/ftp/phase1/analysis_results/integrated_call_sets/ALL.chr2.integrated_phase1_v3.20101123.snps_indels_svs.genotypes.vcf.gz 2:1,000,000-2,000,000 | vcf-subset -c HG01375 | bgzip -c > HG01375.vcf.gz

This command gives you the vcf file for 2:1,000,000-2,000,000 with just the genotypes for HG01375.

To get the coverage for all those sites you would use:

intersectBed -a HG01375.vcf.gz -b coverage.bg -wb > depth_numbers.vcf

You can find more information about bed file formats please see the Ensembl File Formats Help.

For more information you may wish to look at our documentation about data slicing.

Related questions:

Where can I find a list of the sequencing and analysis done for each individual?


Our data portal has a page for each sample. At the bottom of the page, the various data collections that the sample is present in are listed in tabs. Each tab then lists the available files for that sample, including seqeunce data, genotype arrays, alignments and VCFs.

An example is the page for NA12878. Sample IDs can be entered in the search box to locate a given sample.

To understand the data available for larger groups of samples, the samples and population tabs of the portal can be used to explore available data.

Related questions:

Why are there duplicate calls in the phase 3 call set?


The phase 3 VCF files released in June 2014 contain overlapping and duplicate sites.

This is due to an error in the processing pipeline used when sets of variant calls were combined. Originally, all multi-allelic sites were seperated into individual lines in the VCF file during the pipeline but the recombination process did not always succeed, leaving us with a small number of sites with overlapping or duplicate call records. This is most commonly seen in chromosome X.

The simplest solution to this is to ignore duplicate sites in any analysis. If you wish to use one or both of a pair of duplicate sites in your own analysis, you should use the GRCh37 alignment files to recall the genotypes of interest in the individuals you are interested in to resolve the conflict.

Related questions:

Why do some of your vcf genotype files have genotypes of ./. in them?


Our August 2010 call set represents a merge of various different independent call sets. Not all the call sets in the merge had genotypes associated with them, as this merge was carried out using a predefined rules which has led to individuals or whole variant sites having no genotype and this is described as ./. in vcf 4.0. In our November 2010 call set and all subsequent call sets all sites have genotypes for all individuals for chr1-22 and X.

Related questions:

Why is the allele frequency different from allele count/allele number?


In some early main project releases the allele frequency (AF) was estimated using additional information like LD, mapping quality and Haplotype information. This means in these releases the AF was not always the same as allele count/allele number (AC/AN). In the phase 1 release AF should always match AC/AN rounded to two decimal places.

Related questions: