> For the complete documentation index, see [llms.txt](https://academy.dnanexus.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://academy.dnanexus.com/public-datasets-on-the-dnanexus-platform/validation-ready-accelerator/clinvar.md). # ClinVar ## Necessary Disclaimers and Legal The user is responsible for reviewing and complying with the license requirements of the software, and data referenced in this documentation. Users are responsible for the costs associated with analyzing data, software and its storage in their project spaces. Instance type availability and pricing are subject to the contract between the user or the user’s organization and DNAnexus. ## Citation for clinVar * Paper: * Data download: * Summary statistic: * Website: [www.ncbi.nlm.nih.gov/clinvar/](http://www.ncbi.nlm.nih.gov/clinvar/)) ## Overview ClinVar is a free, publicly accessible database that collects and shares information on human genetic variants and their links to disease. With over 3 million variants submitted by more than 2,800 organizations worldwide, it serves as a central resource for clinical genetics labs, research groups, and expert panels. Its primary purpose is to help determine whether observed genetic variants in a patient sample have established clinical relevance. Most data comes from clinical sequencing labs that report variants alongside patient phenotypes. Recently, ClinVar expanded its classification system to include germline variants, oncogenicity, and clinical impact for somatic variants, making it even more useful for both clinical and research applications. ClinVar distributes variant data in genome build–specific directories (GRCh37 and GRCh38). Each release provides VCF files containing clinically annotated variants under 10 kb, enriched with metadata such as allele frequencies, disease associations, and classification details. To support validation and efficient use, accompanying index (.tbi) and checksum (.md5) files are included. Updates are produced weekly, with monthly releases archived for long-term access. For guidance on interpreting the dataset and its fields, see the README\_VCF.txt file. ## clinVar Data on DNAnexus platform The March 9, 2026 ClinVar VCF release is now available on our platform. Two genome build folders, GRCh37 and GRCh38, contain the relevant files. Each directory includes the core clinical VCF files and the companion “papu” VCF files, which cover variants in PAR regions, alternate loci, patches, and unplaced contigs. Index (.tbi) and checksum (.md5) files are also provided to ensure integrity and efficient access. Please access data [here on the platform](https://platform.dnanexus.com/panx/projects/J3JyY6j030gzQypGpk273241/data/ClinVar). ``` clinvar/dataset/ ├── vcf_GRCh37/ │ ├── clinvar_20260309.vcf.gz # timestamped release file │ ├── clinvar.vcf.gz # same file, standardized name (no timestamp) │ ├── *.tbi # index files │ ├── *.md5 # checksum files ├── vcf_GRCh38/ │ ├── clinvar_20260309.vcf.gz │ ├── clinvar.vcf.gz │ ├── *.tbi │ ├── *.md5 └── README_VCF.txt ``` ## How to use clinVar data in nf-core/sarek pipeline ### Variant annotation in nf-core/sarek: The nf-core/sarek workflow uses the following tools for variant annotation (): * snpEff * snpSift (available since version 3.8.0 Feb 10) * bcftools annotate * VEP In the nf-core/sarek pipeline, ClinVar can be utilized in three annotation tools except snpEff ### VEP Cache v115 The Ensembl Variant Effect Predictor (VEP) cache is a pre-built local repository that enables high-throughput, offline variant annotation. Sarek pipeline uses VEP cache for variant annotation and allows users to specify their interested cache version via the --vep\_cache\_version parameter, with Sarek automatically pulling the corresponding cache from the nf-core S3 bucket s3://annotation-cache/vep\_cache/ if no local cache path is provided. It is essential to ensure that the VEP tool version (--vep\_version) and the cache version (--vep\_cache\_version) are identical. Please refer to the VEP[ cache blog](https://www.ensembl.info/2020/10/23/cool-stuff-ensembl-vep-can-do-whats-in-the-cache-and-how-does-vep-use-it/) and [office document](https://asia.ensembl.org/info/docs/tools/vep/script/vep_cache.html?#cache) for more information about VEP cache. The latest nf-core/sarek pipeline (version 3.8.1) runs on VEP Cache v115, which compiles ClinVar (Feb 2025), gnomAD v4.1 (Exomes/Genomes), dbSNP 156, and COSMIC 101 into a single, high-performance resource. It also features GENCODE 49 gene models and functional scores from SIFT and PolyPhen-2. Detailed metadata regarding these datasets and population-specific frequencies can be found in the provided info.txt file ``` # VEP Cache 115 Configuration Summary (from info.txt file) Species: Homo sapiens (GRCh38.p14) Annotations: - Gene_Models: GENCODE 49 - Variant_Frequencies: - gnomAD_v4.1 (Exomes & Genomes) - 1000Genomes_Phase3 - Clinical_Databases: - ClinVar_202502 - COSMIC_101 - dbSNP_156 - HGMD-PUBLIC_20204 - Impact_Scores: - SIFT_6.2.1 - PolyPhen_2.2.3 - Regulation: Ensembl_RegBuild_1.0 ``` In addition to the ClinVar data folder, we provide the VEP Cache v115 folder, which is compatible with the nf-core/sarek pipeline on DNAnexus. Users can utilize this resource by specifying the directory path in the --vep\_cache parameter as shown in the example below. ``` vep_cache dx://project-xxx:/sarek_dataset/vep_cache/ ``` ### SnpSift SnpSift annotates VCF files with custom annotation databases (e.g., dbSNP, gnomAD, ClinVar). To enable it, add “snpsift” to --tools and provide a CSV samplesheet via --snpsift\_databases. The CSV samplesheet specifies annotation databases. See [assets/snpsift\_databases\_example.csv](https://github.com/nf-core/sarek/blob/master/assets/snpsift_databases_example.csv) Here is our example: ```` ```csv vcf,tbi,fields,prefix,vardb /path/to/clinvar.vcf.gz,/path/to/clinvar.vcf.gz.tbi,ALLELEID;CLNDN;ORIGIN;CLNVC;CLNSIGCONF,ClinVar_, /path/to/gnomad.exomes.v4.1.sites.chr2.vcf.gz,/path/to/gnomad.exomes.v4.1.sites.chr2.vcf.gz.tbi,AF;AF_afr;AF_amr;cadd_phred;sift_max;revel_max,gnomAD_, /path/to/gnomad.exomes.v4.1.sites.chr21.vcf.gz,/path/to/gnomad.exomes.v4.1.sites.chr21.vcf.gz.tbi,AF;AF_afr;AF_amr;cadd_phred;sift_max;revel_max,gnomAD_, ``` ```` In the above example, replace /path/to/ with the actual directory where your database files are stored, such as clinvar.vcf.gz and the gnomAD per-chromosome VCF files. ### bcftools annotate To annotate variants with ClinVar using BCFtools in Sarek, you must provide four parameters: --bcftools\_annotations and --bcftools\_annotations\_tbi for the ClinVar VCF and its index; --bcftools\_columns for a file specifying the INFO fields to extract (e.g., CLNSIG, CLNDN); and --bcftools\_header\_lines for VCF header definitions. Although not required by BCFtools itself, these header lines are essential for Sarek's input validation. For --bcftools\_columns, users can follow this example config files to annotate using all available fields in the INFO column ``` process { withName: 'NFCORE_SAREK:SAREK:VCF_ANNOTATE_ALL:BCFTOOLS_ANNOTATE' { ext.args = { '--columns INFO --output-type z --write-index=tbi' } } } ``` A critical consideration is chromosome naming consistency. If the ClinVar file uses numeric names (1, 2) while the input VCF uses the 'chr' prefix (chr1, chr2), the process will fail. To resolve this, users need to manually rename either the clinvar file or the input vcf file. The command is \`bcftools annotate --rename-chrs chr\_rename.txt -Oz -o input\_chr\_renamed.vcf.gz input.vcf.gz\` ``` # example: how to change vcf_file to the name of the input vcf file vcf_file="HCC1395T_vs_HCC1395N.freebayes.filtered.bcftools_filtered.vcf.gz" basename=$(basename ${vcf_file} .vcf.gz) cmd="tabix ${vcf_file}; \ bcftools query -f '%CHROM\\n' ${vcf_file} | uniq > chr.txt; \ awk '{print \$0, substr(\$0, 4)}' chr.txt > chr_replace.txt; \ bcftools annotate --rename-chrs chr_replace.txt ${vcf_file} -Oz -o ${basename}_chr_replaced.vcf.gz; \ tabix ${basename}_chr_replaced.vcf.gz; \ rm chr.txt ${vcf_file}.tbi" dx run swiss-army-knife \ -iin="project-xxx:/ClinVar/dataset/vcf_GRCh38/clinvar.vcf.gz" \ -iin="project-xxx:/ClinVar/dataset/vcf_GRCh38/clinvar.vcf.gz.tbi" \ -iin="project-xxx:/path/to/results/VAL001/${vcf_file}" \ -icmd="$cmd" \ --name "rename_chromosomes" ``` Note that BCFtools supports only one annotation database per run; for multiple databases, VEP or SnpSift are better alternatives.