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<h1 id="gcp-sarscov2-public-dataset-prog">GCP SARS-CoV-2 Public Dataset Program - quick start guide</h1>
<div class="toc">
<ul>
<li><a href="#introduction">Introduction</a></li>
<li><a href="#open-bucket-contents">Open Bucket Contents</a></li>
<li><a href="#querying-the-metadata-to-find-se">Querying the Metadata to find Sequence of Interest</a><ul>
<li><a href="#example-queries-that-can-be-used">Example queries that can be used in the BigQuery console</a><ul>
<li><a href="#filtering-based-on-genomic-posit">Filtering based on genomic position on the reference sequence, NC_045512.2:</a></li>
<li><a href="#filter-for-runs-with-a-specific-">Filter for runs with a specific mutation:</a></li>
<li><a href="#filtering-based-on-read-support">Filtering based on read support:</a></li>
<li><a href="#filtering-based-on-sarscov2-samp">Filtering based on SARS-CoV-2 samples derived metagenomic/metatranscriptomic libraries:</a></li>
<li><a href="#filtering-based-on-organism-to-f">Filtering based on organism to find only runs which were not submitted as SARS-CoV-2, but where it was detected:</a></li>
<li><a href="#filter-for-all-variations-called">Filter for all variations called from samples collected in the United States after '2022-06-01':</a></li>
</ul>
</li>
</ul>
</li>
<li><a href="#viewing-and-navigating-the-open-">Viewing and Navigating the Open Bucket</a></li>
<li><a href="#using-the-sequence-data-from-the">Using the Sequence Data from the Command Line</a></li>
<li><a href="#notes-on-ncbigenerated-variants">Notes on NCBI-generated variants</a></li>
<li><a href="#additional-resources">Additional Resources</a></li>
<li><a href="#contact-sra">Contact SRA</a></li>
</ul>
</div>
<h2 id="introduction">Introduction</h2>
<p>The NCBI COVID-19 Genome Sequence Dataset (<a target="_blank" title="The NCBI COVID-19 Genome Sequence Dataset" href="https://console.cloud.google.com/storage/browser/nih-sequence-read-archive">https://console.cloud.google.com/storage/browser/nih-sequence-read-archive</a>)
is hosted in Google Cloud Storage and is available for free use and download with no egress charges. It includes both
sequence data and searchable metadata from the Sequence Read Archive. The data and metadata encompass Runs identified
to contain Coronaviridae using a kmer-based approach to organismal content analysis
(<a title="SRA Detection Tool" href="/sra/docs/sra-detection-tool/">SRA Detection Tool</a>). This set includes files in both
the originally submitted data format as well as normalized <a title="SRA file formats" href="/sra/docs/sra-data-formats/">SRA file formats</a> for each Run.
NCBI has also made annotated variation metadata for this set available in BigQuery to
allow rapid, SQL-based searching either manually or programmatically in the cloud. </p>
<h2 id="open-bucket-contents">Open Bucket Contents</h2>
<p>The <strong>run</strong> directory contains the normalized SRA sequence data, organized by Run accession and accessible
via the SRA Toolkit (<a target="_blank" title="The SRA Toolkit" href="https://github.com/ncbi/sra-tools/wiki">https://github.com/ncbi/sra-tools/wiki</a>). </p>
<p>The <strong>sra-src</strong> directory contains the originally submitted sequence data files, also organized by Run accession. </p>
<p>The <strong>SARS_COV_2</strong> directory contains the variation and VIGOR3 annotation information for these Runs in JSON format. </p>
<p>The <strong>vcf</strong> directory contains the NCBI-generated VCF files for these data, organized by Run accession. </p>
<h2 id="querying-the-metadata-to-find-se">Querying the Metadata to find Sequence of Interest</h2>
<p>Annotated variation metadata (<a title="SRA CoV-2 Variant Calling" href="/sra/docs/sars-cov-2-variant-calling/">https://www.ncbi.nlm.nih.gov/sra/docs/sars-cov-2-variant-calling/</a>)
for this SARS-CoV-2 dataset has been deposited into BigQuery as a table called <strong>annotated_variations</strong> to provide the
bioinformatics community with access to this information. This table can be used to answer questions directly
or to identify runs of interest for further analysis. You can find a list of fields
available in this table here: <a title="SRA Cloud-based Annotated Variations Table" href="/sra/docs/sra-cloud-based-annotated-variations-table/">https://www.ncbi.nlm.nih.gov/sra/docs/sra-cloud-based-annotated-variations-table/</a>. </p>
<p>After finding a set of Runs you would like to analyze, you can move on to download or dump the
sequence data in your format of choice. We generally recommend querying the metadata using BigQuery,
however the underlying data files are available in JSON format from the open bucket as well
(in the <strong>SARS_COV_2</strong> directory; <em>gs://nih-sequence-read-archive/SARS_COV_2/annotated_variations</em>).
This public dataset is included in BigQuery's 1TB/mo of free tier processing
(<a target="_blank" title="https://cloud.google.com/free/docs/gcp-free-tier/#bigquery" href="https://cloud.google.com/free/docs/gcp-free-tier/#bigquery">https://cloud.google.com/free/docs/gcp-free-tier/#bigquery</a>), meaning each user receives 1TB of free BigQuery. <br />
processing each month that can be used to run queries on this metadata. </p>
<p>To get started using a BigQuery public dataset, you must first create or select a project. If you want to use more than
the free tier of data, you must also enable billing. To query this data in the BigQuery web interface,
log in to the Google Cloud Platform, then from the project selector page
(<a target="_blank" title="Google Cloud Platform Dashboard" href="https://console.cloud.google.com/projectselector2/home/dashboard">https://console.cloud.google.com/projectselector2/home/dashboard</a>), select or create a <strong>Google Cloud project</strong>.
If you don't plan to keep the resources that you create during this process- you may create a project, then delete
it when done, which removes all resources associated with the project. </p>
<p>Next, navigate to the BigQuery interface by either searching for it in the search bar at the top of the screen or
navigating there directly: <a target="_blank" title="Google Cloud BigQuery" href="https://console.cloud.google.com/bigquery">https://console.cloud.google.com/bigquery</a>. Then click the <strong>Add Data</strong> button on the
upper left side of the screen in the Explorer panel, select <strong>Pin a project by name</strong>, paste <strong>bigquery-public-data</strong>
into the "Project name" box and click "Pin". This will bring you to a BigQuery window where the <strong>bigquery_public_data</strong>
project will be shown in the left-hand <strong>Explorer</strong> section. </p>
<div class="shadowing"><a data-jig="ncbipopper" data-resizable="false" href="#target1"><img src="/core/assets/sra/images/triangle_run.png" alt="triangle_run.png" width="600" /></a></div>
<div class="shadowing" id="target1"><img src="/core/assets/sra/images/triangle_run.png" alt="triangle_run.png" width="900" /></div>
<p>From there, click the triangular expand node to the left of the project
entry to see the list of datasets available (you will likely need to click the <strong>More Results</strong>
link when you reach the bottom of the list to show the full list), then scroll down to find the
<strong>nih_sequence_read</strong> dataset. Click the triangular expand node to the left of the dataset to see the <strong>annotated_variations</strong> table.
Clicking on the table name will open it in the main window. You may then click on the <strong>Schema</strong>, <strong>Details</strong>, and
<strong>Preview</strong> tabs to further explore the contents of the table. The Schema tab gives information about the name of
each field in the table and how that field is encoded (string, integer). The Details tab provides information
about the data underlying the table, such as the last time it was updated and how many rows the table contains.
The Preview tab shows you the first few rows of the table so you can see what the data actually look like.
Finally, click the <strong>Query</strong> button to open up a new query edit window prefilled for that table, where you can type
in your own query from scratch or copy/paste one of the examples below. </p>
<div class="shadowing"><a data-jig="ncbipopper" data-resizable="false" href="#target2"><img src="/core/assets/sra/images/annotated_var_schema_red.png" alt="annotated_var_schema_red.png" width="600" /></a></div>
<div class="shadowing" id="target2"><img src="/core/assets/sra/images/annotated_var_schema_red.png" alt="annotated_var_schema_red.png" width="900" /></div>
<p>After entering a valid query in the window, you will see a message like <strong>This query will process XX when run</strong> in
the upper right corner of the query window. This tells you how much data will be processed to run the query,
which determines the cost of the query (<a target="_blank" title="Google Cloud BigQuery pricing" href="https://cloud.google.com/bigquery/pricing">https://cloud.google.com/bigquery/pricing</a>) or how much of your allotted
free tier data processing it will consume. When you are ready to proceed you can click the <strong>Run</strong> button in the upper
left corner of the interface to run the query. The results will be displayed underneath the query window and you can save
a local copy using the <strong>Save Results</strong> button displayed at the top of that section. </p>
<div class="shadowing"><a data-jig="ncbipopper" data-resizable="false" href="#target3"><img src="/core/assets/sra/images/Ann_var_run_red.png" alt="Ann_var_run_red.png" width="600" /></a></div>
<div class="shadowing" id="target3"><img src="/core/assets/sra/images/Ann_var_run_red.png" alt="Ann_var_run_red.png" width="900" /></div>
<h3 id="example-queries-that-can-be-used">Example queries that can be used in the BigQuery console</h3>
<h4 id="filtering-based-on-genomic-posit">Filtering based on genomic position on the reference sequence, <a title="NC_045512.2" href="/nuccore/NC_045512.2">NC_045512.2</a>:</h4>
<div class="gray-box">
<span class="code">
SELECT * <br />
FROM `bigquery-public-data.nih_sequence_read.annotated_variations` <br />
WHERE POS &lt; 1000 and POS &gt; 2000 <br />
</span></div>
<h4 id="filter-for-runs-with-a-specific-">Filter for runs with a specific mutation:</h4>
<div class="gray-box">
<span class="code">
SELECT distinct run <br />
FROM `bigquery-public-data.nih_sequence_read.annotated_variations` <br />
WHERE variation = "E484K" <br />
</span></div>
<h4 id="filtering-based-on-read-support">Filtering based on read support:</h4>
<div class="gray-box">
<span class="code">
SELECT run<br />
FROM `bigquery-public-data.nih_sequence_read.annotated_variations` <br />
WHERE DP &lt;= 100 and G_AD_2 &lt;49 AND G_AD_2/DP &lt;=0.15 <br />
</span></div>
<p>Queries of the annotated variation table can be combined with the <a title="SRA metadata table" href="/sra/docs/sra-cloud-based-metadata-table/">SRA metadata table</a>,
which contains library and sample metadata for all public Runs in SRA: </p>
<h4 id="filtering-based-on-sarscov2-samp">Filtering based on SARS-CoV-2 samples derived metagenomic/metatranscriptomic libraries:</h4>
<div class="gray-box">
<span class="code">
SELECT distinct run <br />
FROM `bigquery-public-data.nih_sequence_read.annotated_variations`<br />
WHERE run in<br />
(SELECT acc<br />
FROM `nih-sra-datastore.sra.metadata`<br />
WHERE organism = "Severe acute respiratory syndrome coronavirus 2"<br />
and librarysource in ("METAGENOMIC","METATRANSCRIPTOMIC"))<br />
</span></div>
<h4 id="filtering-based-on-organism-to-f">Filtering based on organism to find only runs which were not submitted as SARS-CoV-2, but where it was detected:</h4>
<div class="gray-box">
<span class="code">
SELECT run, variation <br />
FROM `bigquery-public-data.nih_sequence_read.annotated_variations` <br />
WHERE run in <br />
 <br />
(SELECT acc <br />
FROM `nih-sra-datastore.sra.metadata` <br />
WHERE organism != "Severe acute respiratory syndrome coronavirus 2") <br />
</span></div>
<p>Filter for runs with a specific mutation, then list the count and geographic location where the sample was
collected in order of decreasing frequency: </p>
<div class="gray-box">
<span class="code">
SELECT distinct geo_loc_name_country_calc, count (geo_loc_name_country_calc) as count <br />
FROM `nih-sra-datastore.sra.metadata` <br />
WHERE acc in <br />
(SELECT distinct run
FROM `bigquery-public-data.nih_sequence_read.annotated_variations` <br />
WHERE variation = "E484K" ) <br />
GROUP BY geo_loc_name_country_calc <br />
ORDER BY count DESC <br />
</span></div>
<h4 id="filter-for-all-variations-called">Filter for all variations called from samples collected in the United States after '2022-06-01':</h4>
<div class="gray-box">
<span class="code">
SELECT run, variation <br />
FROM `bigquery-public-data.nih_sequence_read.annotated_variations` <br />
WHERE run in <br />
(SELECT acc <br />
FROM `nih-sra-datastore.sra.metadata` <br />
WHERE collection_date_sam &lt; '2022-06-01' and geo_loc_name_country_calc = 'USA')<br />
</span></div>
<p>The data in these tables is updated over time as more Runs containing SARS-CoV-2 are submitted to SRA, processed,
and included. If you would like to pin the SRA <strong>Metadata</strong> table for future use, the process is similar to pinning
the annotated variations table above. From the BigQuery interface, click the <strong>Add data</strong> button on the upper left side
of the screen in the Explorer panel. Next, select <strong>Pin a project by name</strong>, paste <strong>nih-sra-datastore</strong> into the <strong>Project name</strong>
box and click <strong>Pin</strong>. It will now appear on the left side of the page in the Explorer panel. The list of fields in this table
is available here: <a title="SRA metadata table" href="/sra/docs/sra-cloud-based-metadata-table/">SRA metadata table</a>. </p>
<p>You can find more information on using public datasets here: <a target="_blank" title="BiQuery public data" href="https://cloud.google.com/bigquery/public-data">https://cloud.google.com/bigquery/public-data</a>. </p>
<p>A video tutorial with more in-depth background and examples of using BigQuery on SRA metadata is available here:
<a target="_blank" title="https://youtu.be/DkNz-RCCm-M" href="https://youtu.be/DkNz-RCCm-M">https://youtu.be/DkNz-RCCm-M</a>. </p>
<h2 id="viewing-and-navigating-the-open-">Viewing and Navigating the Open Bucket</h2>
<p>For users who wish to browse the dataset or manually download a few files, the data files can be viewed on
the web using the cloud console here:
<a target="_blank" title="https://console.cloud.google.com/storage/browser/nih-sequence-read-archive" href="https://console.cloud.google.com/storage/browser/nih-sequence-read-archive">https://console.cloud.google.com/storage/browser/nih-sequence-read-archive</a>. </p>
<p>For users who wish to browse the dataset or manually download a few files, the data files can be viewed on
the web using the cloud console here:
<a target="_blank" title="https://console.cloud.google.com/storage/browser/nih-sequence-read-archive" href="https://console.cloud.google.com/storage/browser/nih-sequence-read-archive">https://console.cloud.google.com/storage/browser/nih-sequence-read-archive</a>. </p>
<div class="shadowing"><a data-jig="ncbipopper" data-resizable="false" href="#target4"><img src="/core/assets/sra/images/run_bucket_red.png" alt="run_bucket_red.png" width="600" /></a></div>
<div class="shadowing" id="target4"><img src="/core/assets/sra/images/run_bucket_red.png" alt="run_bucket_red.png" width="900" /></div>
<p>If you are interested in specific accessions, you can use the <strong>Filter</strong>
box to filter the displayed contents of the directory. </p>
<div class="shadowing"><a data-jig="ncbipopper" data-resizable="false" href="#target5"><img src="/core/assets/sra/images/run_bucket_filter_red.png" alt="run_bucket_filter_red.png" width="600" /></a></div>
<div class="shadowing" id="target5"><img src="/core/assets/sra/images/run_bucket_filter_red.png" alt="run_bucket_filter_red.png" width="900" /></div>
<p>The bucket/object path for any level of the directory structure can be copied to the clipboard by clicking the copy icon
shown next to the path schema near the top of the bucket page. </p>
<div class="shadowing"><a data-jig="ncbipopper" data-resizable="false" href="#target6"><img src="/core/assets/sra/images/run_bucket_red2.png" alt="run_bucket_red2.png" width="600" /></a></div>
<div class="shadowing" id="target6"><img src="/core/assets/sra/images/run_bucket_red2.png" alt="run_bucket_red2.png" width="900" /></div>
<p>You can also click on any object in the bucket to go to the object details page that lists the public URL and gsutil URI,
which can be used to move or download the data. Either of these paths can be copied by clicking on the copy
icon next to their respective sections of the object details page. </p>
<div class="shadowing"><a data-jig="ncbipopper" data-resizable="false" href="#target7"><img src="/core/assets/sra/images/object_details_red.png" alt="object_details_red.png" width="600" /></a></div>
<div class="shadowing" id="target7"><img src="/core/assets/sra/images/object_details_red.png" alt="object_details_red.png" width="900" /></div>
<h2 id="using-the-sequence-data-from-the">Using the Sequence Data from the Command Line</h2>
<p>For data in normalized SRA format (files in the <strong>run</strong> directory), the SRA Toolkit is required to access the data.
If you are working on a Google Cloud VM
(<a title="SRA Google cloud" href="/sra/docs/SRA-Google-Cloud/">https://www.ncbi.nlm.nih.gov/sra/docs/SRA-Google-Cloud/</a>), the toolkit<br />
will automatically pull the files from cloud storage with no need to manually copy them (be sure to enable
<strong>report cloud instance identity</strong> from the <strong>GCP</strong> tab of the configuration utility during setup).<br />
You can find instructions for installing and configuring the toolkit here: </p>
<p><a target="_blank" title="Installing SRA Toolkit" href="https://github.com/ncbi/sra-tools/wiki/02.-Installing-SRA-Toolkit">https://github.com/ncbi/sra-tools/wiki/02.-Installing-SRA-Toolkit</a> </p>
<p><a target="_blank" title="Configuring SRA Toolkit" href="https://github.com/ncbi/sra-tools/wiki/03.-Quick-Toolkit-Configuration">https://github.com/ncbi/sra-tools/wiki/03.-Quick-Toolkit-Configuration</a> </p>
<p>Once installed and configured you can access these data by accession using the SRA Toolkit.
For instance, to generate fastq formatted
files from the normalized data, the <strong>fasterq-dump</strong> tool can be used: </p>
<div class="gray-box">
<span class="code">fasterq-dump SRR10003114 </span> </div>
<p>The default output will be separate forward and reverse fastq files for each Run
(if the data are paired-end), written to the current working directory. The toolkit accepts space
delimited sets of Run accessions directly on the command line or they can be provided in
a text file, one accession per line, using the <strong><code>--option-file</code></strong> flag. </p>
<p>If you prefer to move files to your own storage, the files from the open bucket can be copied programmatically
using the <strong>gsutil</strong> package (<a target="_blank" title="https://cloud.google.com/storage/docs/gsutil)" href="https://cloud.google.com/storage/docs/gsutil">https://cloud.google.com/storage/docs/gsutil)</a> and the gsutil URI: </p>
<div class="gray-box">
<span class="code">gsutil cp gs://nih-sequence-read-archive/sra-src/SRR10003816/FIB_oil3_1.fq.gz [destination]</span> </div>
<p>The gsutil URI can be generated by concatenating the bucket path (<strong>gs://nih-sequence-read-archive/</strong>) <br />
with the object ID (eg: <strong>run/SRR10003816/SRR10003816</strong>): </p>
<div class="gray-box">
<span class="code">gs://nih-sequence-read-archive/run/SRR10003816/SRR10003816</span> </div>
<p>Alternatively, these files can be downloaded via WGET or similar protocols.
You can construct the HTTP address by replacing the <strong>GS://</strong> prefix of the URI with: </p>
<p><a target="_blank" title="https://storage.googleapis.com/" href="https://storage.googleapis.com/">https://storage.googleapis.com/</a> </p>
<p>to generate a download URL, eg: </p>
<p><a target="_blank" title="https://storage.googleapis.com/nih-sequence-read-archive/run/SRR10003816/SRR10003816" href="https://storage.googleapis.com/nih-sequence-read-archive/run/SRR10003816/SRR10003816">https://storage.googleapis.com/nih-sequence-read-archive/run/SRR10003816/SRR10003816</a> </p>
<h2 id="notes-on-ncbigenerated-variants">Notes on NCBI-generated variants</h2>
<p>The details of variant calling for these runs can be found here: </p>
<p><a title="SRA Cov-2 Variant Calling" href="/sra/docs/sars-cov-2-variant-calling/">https://www.ncbi.nlm.nih.gov/sra/docs/sars-cov-2-variant-calling/</a> </p>
<p>The annotation was carried out using VIGOR3:</p>
<p><a target="_blank" title="https://pubmed.ncbi.nlm.nih.gov/22669909/" href="https://pubmed.ncbi.nlm.nih.gov/22669909/">https://pubmed.ncbi.nlm.nih.gov/22669909/</a> </p>
<h2 id="additional-resources">Additional Resources</h2>
<p>If you would like to download the raw underlying metadata or manually import it as a custom table in BigQuery,
the location of the raw metadata files in JSON format for the annotated variations table can be found below:</p>
<p><code>gs://nih-sequence-read-archive/SARS_COV_2/annotated_variations/*</code></p>
<p>Full table definitions can be found here:</p>
<p><a title="SRA cloud-based annotated variations table/" href="https://www.ncbi.nlm.nih.gov/sra/docs/sra-cloud-based-annotated-variations-table/">https://www.ncbi.nlm.nih.gov/sra/docs/sra-cloud-based-annotated-variations-table/</a> </p>
<p><a title="SRA cloud-based metadata table/" href="https://www.ncbi.nlm.nih.gov/sra/docs/sra-cloud-based-metadata-table/">https://www.ncbi.nlm.nih.gov/sra/docs/sra-cloud-based-metadata-table/</a> </p>
<hr />
<h2 id="contact-sra">Contact SRA</h2>
<p>Contact SRA staff for assistance at <a href="mailto:sra@ncbi.nlm.nih.gov?subject=SRA%20question&amp;body=Dear%20SRA%20staff">sra@ncbi.nlm.nih.gov</a> </p>
</div>
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<h2 data-heading="h2" data-no-toc="true">Getting Started</h2>
<ul>
<li><a title="SRA Getting Started" href="/sra/docs/">Getting Started</a> </li>
</ul>
<h2 data-heading="h2" data-no-toc="true">Cloud Quick Start</h2>
<ul>
<li><a title="SRA Cloud getting started" href="/sra/docs/sra-cloud">Cloud Introduction</a> </li>
<li><a target="_blank" title="SRA on YouTube: Tutorials" href="https://www.youtube.com/playlist?list=PL7dF9e2qSW0ZZci13mHSKZYis3MV4Mdoa">YouTube Tutorials</a> </li>
<li><a title="GCP SARS-CoV-2 Public Dataset Guide" href="/sra/docs/gcp-pdp-guide">GCP SARS-CoV-2 Public Dataset Guide</a> </li>
<li><a title="SRA Cloud Access Costs" href="/sra/docs/sra-cloud-access-costs">SRA Cloud Access Costs</a> </li>
</ul>
<h2 data-heading="h2" data-no-toc="true">Setting Up</h2>
<ul>
<li><a title="SRA Google Cloud" href="/sra/docs/SRA-Google-Cloud">Set up Google Cloud</a> </li>
<li><a title="SRA Amazon Cloud" href="/sra/docs/sra-aws-download/">Set up Amazon Cloud</a> </li>
<li><a title="SRA in BigQuery" href="/sra/docs/sra-bigquery">Set up BigQuery</a> </li>
<li><a title="SRA in Athena" href="/sra/docs/sra-athena">Set up Athena</a> </li>
</ul>
<h2 data-heading="h2" data-no-toc="true">Cloud Data Access</h2>
<ul>
<li><a title="Download SRA sequences from Entrez search results" href="/sra/docs/sradownload">Download Guide</a> </li>
<li><a title="Data Delivery to cloud bucket" href="/sra/docs/data-delivery">Cloud Data Delivery Service</a> </li>
</ul>
<h2 data-heading="h2" data-no-toc="true">Accessing dbGAP</h2>
<ul>
<li><a title="Download dbGAP from cloud" href="/sra/docs/sra-dbGAP-cloud-download">Download dbGAP with JWT</a> </li>
</ul>
<h2 data-heading="h2" data-no-toc="true">Search</h2>
<ul>
<li><a title="SRA cloud-based search" href="/sra/docs/sra-cloud-based-examples">Cloud-based Search</a> </li>
<li><a title="SRA in BigQuery" href="/sra/docs/sra-bigquery-examples">Search in BigQuery</a> </li>
<li><a title="SRA in Athena" href="/sra/docs/sra-athena-examples">Search in Athena</a> </li>
</ul>
<h2 data-heading="h2" data-no-toc="true">SRA Analysis</h2>
<ul>
<li><a title="SRA Aligned Read Format" href="/sra/docs/sra-aligned-read-format">SRA Aligned Read Format</a> </li>
<li><a title="SRA SARS-CoV-2 Detection Tool" href="/sra/docs/sra-detection-tool">SARS-CoV-2 Detection Tool</a> </li>
<li><a title="SARS-CoV-2 Variant Calling" href="/sra/docs/sars-cov-2-variant-calling">SARS-CoV-2 Variant Calling</a> </li>
<li><a title="SRA Taxonomy Analysis Tool" href="/sra/docs/sra-taxonomy-analysis-tool">SRA Taxonomy Analysis Tool</a> </li>
</ul>
<h2 data-heading="h2" data-no-toc="true">SRA Data Formats</h2>
<ul>
<li><a title="SRA Data Formats" href="/sra/docs/sra-data-formats">SRA Data Formats</a> </li>
<li><a title="Data Format FAQ" href="/sra/docs/data-format-faq">Data Format FAQ</a> </li>
</ul>
</div>
</div>
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