Benchmark datasets for WGS analysis of SARS-CoV-2.
Technical Outreach and Assistance for States Team (TOAST) developed benchmark datasets for SARS-CoV-2 sequencing which are designed to help users at varying stages of building sequencing capacity. It consists of six datasets summarized in the table below, each chosen to represent a different use case.
| Dataset | Name | Description | Intended Use | tsv name | Primer Set | Reference |
|---|---|---|---|---|---|---|
| 1 | Boston Outbreak | A cohort of 63 samples from a real outbreak with three introductions, Illumina platform, metagenomic approach | To understand the features of virus transmission during real outbreak setting, metagenomic sequencing | sars-cov-2-SNF-A.tsv | NA | Lemieux et al. |
| 2 | CoronaHiT rapid | A cohort of 39 samples prepared by different wet-lab approaches and sequenced at two platforms (Illumina vs MinIon) with MinIon running for 18 hrs, amplicon-based approach | To verify that a bioinformatics pipeline finds virtually no differences between platforms of the same genome, outbreak setting | sars-cov-2-coronahit-rapid.tsv | ARTIC_V3 | Baker et al. |
| 3 | CoronaHiT routine | A cohort of 69 samples prepared by different wet-lab approaches and sequenced at two platforms (Illumina vs MinIon) with MinIon running for 30 hrs, amplicon-based approach | To verify that a bioinformatics pipeline finds virtually no differences between platforms of the same genome, routinue surveillance | sars-cov-2-coronahit-routine.tsv | ARTIC_V3 | Baker et al. |
| 4 | VOI/VOC lineages | A cohort of 16 samples from 10 representative CDC defined VOI/VOC lineages as of 06/15/2021, Illumina platform, amplicon-based approach | To benchmark lineage-calling bioinformatics pipeline especially for VOI/VOCs, bioinformatics pipeline validation | sars-cov-2-voivoc.tsv | ARTIC_V3 | This study |
| 5 | Non-VOI/VOC lineages | A cohort of 39 samples from representative non VOI/VOC lineages as of 05/30/2021, Illumina platform, amplicon-based approach | To benchmark lineage-calling pipeline nonspecific to VOI/VOCs, bioinformatics pipeline validation | sars-cov-2-nonvoivoc.tsv | ARTIC_V3: 34, ARTIC_V1: 2, RandomPrimer-SSIV_NexteraXT: 2, NA: 1 | This study |
| 6 | Failed QC | A cohort of 24 samples failed basic QC metrics, covering 8 possible failure scenarios, Illumina platform, amplicon-based approach | To serve as controls to test bioinformatics quality control cutoffs | sars-cov-2-failedQC.tsv | ARTIC_V3: 5, CDC in house multiplex PCR primers (Paden et al.): 19 | This study |
Some methods of installation are maintained by the community. Although we do not have direct control over them, we would like to list them for convenience.
Visit INSTALL.md for these methods.
Grab the latest stable release under the releases tab. If you are feeling adventurous, use git clone! Include the scripts directory in your path. For example, if you downloaded this project into your local bin directory:
$ export PATH=$PATH:$HOME/bin/datasets/scripts
Additionally, ensure that you have the NCBI API key. This key associates your edirect requests with your username. Without it, edirect requests might be buggy. After obtaining an NCBI API key, add it to your environment with
export NCBI_API_KEY=unique_api_key_goes_here
where unique_api_key_goes_here is a unique hexadecimal number with characters from 0-9 and a-f.
You should also set your email address in the
EMAIL environment variable as edirect tries to guess it, which is an error prone process.
Add this variable to your environment with
export EMAIL=my@email.address
using your own email address instead of my@email.address.
In addition to the installation above, please install the following.
- edirect (see section on edirect below)
- sra-toolkit, built from source: https://github.com/ncbi/sra-tools/wiki/Building-and-Installing-from-Source
- Perl 5.12.0
- Make
- wget - Brew users:
brew install wget - sha256sum - Linux-based OSs should have this already; Other users should see the relevant installation section below.
Modified instructions from https://www.ncbi.nlm.nih.gov/books/NBK179288/
sh -c "$(curl -fsSL ftp://ftp.ncbi.nlm.nih.gov/entrez/entrezdirect/install-edirect.sh)"
NOTE: edirect needs an NCBI API key. Instructions can be found at https://ncbiinsights.ncbi.nlm.nih.gov/2017/11/02/new-api-keys-for-the-e-utilities
If you do not have sha256sum (e.g., if you are on MacOS), then try to make the shell function and export it.
function sha256sum() { shasum -a 256 "$@" ; }
export -f sha256sum
This shell function will need to be defined in the current session. To make it permanent for future sessions, add it to $HOME/.bashrc.
To run, you need a dataset in tsv format. Here is the usage statement:
Usage: GenFSGopher.pl -o outdir spreadsheet.dataset.tsv
PARAM DEFAULT DESCRIPTION
--outdir <req'd> The output directory
--compressed Compress files after finishing hashsum verification
--format tsv The input format. Default: tsv. No other format
is accepted at this time.
--layout onedir onedir - Everything goes into one directory
byrun - Each genome run gets its separate directory
byformat - Fastq files to one dir, assembly to another, etc
cfsan - Reference and samples in separate directories with
each sample in a separate subdirectory
--shuffled <NONE> Output the reads as interleaved instead of individual
forward and reverse files.
--norun <NONE> Do not run anything; just create a Makefile.
--numcpus 1 How many jobs to run at once. Be careful of disk I/O.
--citation Print the recommended citation for this script and exit
--version Print the version and exit
--help Print the usage statement and die
There is a field intendedUse which suggests how a particular dataset might be used. For example, Epi-validated outbreak datasets might be used with a SNP-based or MLST-based workflow. As the number of different values for intendedUse increases, other use-cases will be available. Otherwise, how you use a dataset is up to you!
To create your own dataset and to make it compatible with the existing script(s) here, please follow these instructions. These instructions are subject to change.
Start by creating a new Excel spreadsheet with only one tab. Please delete any extraneous tabs to avoid confusion. Then view the specification.
If this project has helped you, please cite both this website and the publication:
Xiaoli L, Hagey JV, et al. "Benchmark datasets for SARS-CoV-2 surveillance bioinformatics." PeerJ 10 (2022): e13821.
DOI: 10.7717/peerj.13821
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