> 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/genome-in-a-bottle-giab.md).
# Genome in a Bottle (GIAB)
## 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.
## Citations for GIAB
Genome in a Bottle (GIAB) is a public-private consortium hosted by the National Institute of Standards and Technology (NIST). For citation guidance, please refer to the official GIAB program page at [www.nist.gov/programs-projects/genome-bottle](http://www.nist.gov/programs-projects/genome-bottle) and the GIAB GitHub repository at [github.com/genome-in-a-bottle/about\_GIAB](http://github.com/genome-in-a-bottle/about_GIAB).
Key publications:
* Zook J et al. Extensive sequencing of seven human genomes to characterize benchmark reference materials. Sci Data. 2016.[ https://www.nature.com/articles/sdata201625](https://www.nature.com/articles/sdata201625)
* Wang Y et al. High-coverage, long-read sequencing of Han Chinese trio reference samples. Sci Data. 2019.[ https://www.nature.com/articles/s41597-019-0098-2](https://www.nature.com/articles/s41597-019-0098-2)
Benchmark VCF and BED files for small variants are publicly available for both GRCh37 and GRCh38 from [GIAB](https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/). We downloaded benchmark resources for all samples, including v4.2.1 for all seven samples and v5.0q for HG002, and made them accessible on the DNAnexus platform.
## Overview
The Genome in a Bottle (GIAB) Consortium’s mission is to establish reliable standards for evaluating whole human genome sequencing technologies and their analysis pipelines. GIAB focuses on characterizing a small set of human genome samples. The initial pilot genome was NA12878 (HG001), a widely used reference sample from the HapMap project. GIAB later expanded its resources to include two family trios, each consisting of a child, father, and mother: one trio of Ashkenazi Jewish ancestry and one trio of Han Chinese ancestry.
### Reference samples
| Sample ID | Sample name/ description |
| --------- | ----------------------------- |
| HG001 | NA12878 / HapMap pilot genome |
| HG002 | Ashkenazim Trio son |
| HG003 | Ashkenazim Trio father |
| HG004 | Ashkenazim Trio mother |
| HG005 | Chinese Trio son |
| HG006 | Chinese Trio father |
| HG007 | Chinese Trio mother |
## GIAB data on the DNAnexus platform
Pre-staged GIAB truth datasets are available on the platform, organized as follows:
```
GIAB/
├── small_variants/
│ ├── GRCh37/ # v4.2.1 (HG001-HG007) + v5.0q_smvar (HG002)
│ └── GRCh38/ # v4.2.1 (HG001-HG007) + v5.0q_smvar (HG002)
└── structural_variants/
├── CMRG_v1.00/
│ ├── GRCh37/ # HG002 CMRG SV truth set
│ └── GRCh38/ # HG002 CMRG SV truth set
├── NIST_SV_v0.6/ # HG002 SV Tier1, GRCh37 only
└── v5.0q/
├── GRCh37/ # HG002 v5.0q_stvar
└── GRCh38/ # HG002 v5.0q_stvar
```
### Small variants
Two truth set versions are available on both GRCh37 and GRCh38:
* v4.2.1 is available for all samples (HG001-HG007). For HG002, HG003, and HG004, an additional BED file with Mendelian inconsistencies excluded (\*\_noinconsistent.bed) is provided. This file excludes regions around Mendelian inheritance errors within the Ashkenazim trio, producing a more conservative set of high-confidence regions. Note that v4.2.1 is deprecated for HG002 and has been superseded by v5.0q. For more information, please check [official v4.2.1 release notes](https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/release/NA12878_HG001/latest/README_v4.2.1.txt).
* v5.0q\_smvar is the latest small variant draft benchmark set for HG002, based on the T2T-HG002 v1.1 assembly. See the Technical Considerations section in the nf-core/variantbenchmarking user guide for known issues when using this truth set. Please refer to [the NIST website](https://www.nist.gov/programs-projects/genome-bottle) for further information.
### Structural variants
Three structural variant truth sets are available, all for HG002:
* NIST\_SV\_v0.6 is the GIAB SV Tier1 benchmark on GRCh37. It contains sequence-resolved SV calls of 50 bp or larger with high-confidence regions. Please refer to [README\_SV\_v0.6.txt](https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/release/AshkenazimTrio/HG002_NA24385_son/NIST_SV_v0.6/README_SV_v0.6.txt) for further information.
* CMRG\_v1.00 is a SV benchmark focused on 273 challenging medically relevant genes on GRCh37 and GRCh38. Please refer to [README\_GIAB\_medical\_gene\_benchmark.md](https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/release/AshkenazimTrio/HG002_NA24385_son/CMRG_v1.00/README_GIAB_medical_gene_benchmark.md) for further information.
* v5.0q\_stvar is the latest structural variant draft benchmark set for HG002 on GRCh37 and GRCh38. Please refer to [NIST\_HG002\_v5.0q\_variant-benchmarksets\_README.md](https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/release/AshkenazimTrio/HG002_NA24385_son/v5.0q/) for further information.
## Accessing GIAB data on the DNAnexus platform
The GIAB truth datasets are pre-staged in the Public Datasets AWS US East project and can be accessed directly without copying. To use the files in your own project, you can copy them from the public project:
1. Create a new project billed to your organization. See [Setting Up a Project](https://academy.dnanexus.com/overview-of-the-platform/setting-up-a-project) for instructions.
2. Go to the Resources tab and find the project "Public Datasets AWS US East". Navigate to the GIAB/ folder.
3. Select the folders and files you need.
4. Click Copy from the top right menu and select the project you created in Step 1.
5. Go to your project to start using the data.
## Using GIAB data with nf-core/variantbenchmarking
The GIAB truth sets available on the DNAnexus platform can be used as input to nf-core/variantbenchmarking via the --truth\_vcf, --truth\_id, and --regions\_bed parameters. Please refer to the nf-core/variantbenchmarking user guide \ for instructions on how to configure and run the pipeline with these truth sets.