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<h1>Documentation</h1>
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<h3>Introduction</h3>
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<div style="text-align: justify">
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<p>
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The clear majority of genome wide association studies (GWAS) associate human diseases with some variants
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residing outside the coding DNA. Only a small fraction of these GWAS-associated noncoding variants are
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causal, many are in regions of high linkage disequilibrium hosting either a causal coding variant or a
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causal noncoding variant of a gene regulatory element. Identifying causal noncoding variants has always been
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a challenging task due to a limited number of methods and tools accurately quantifying the impact of a
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noncoding mutation.
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</p>
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<p>
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A growing body of work has been devoted to the quantification of deleterious effects of noncoding
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mutations using artificial intelligence and deep learning methods. These methods include
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||
<a href="http://www.nature.com/nmeth/journal/v12/n10/full/nmeth.3547.html">DeepSEA</a>,
|
||
<a href="http://www.nature.com/nbt/journal/v33/n8/full/nbt.3300.html">DeepBind</a>, and
|
||
<a href="http://genome.cshlp.org/content/early/2016/05/03/gr.200535.115.abstract">Basset</a> that
|
||
‘deep learn’ regulatory sequence code from big genomics data;
|
||
<a href="http://www.nature.com/ng/journal/v47/n8/full/ng.3331.html">deltaSVM</a>
|
||
and
|
||
<a href="https://academic.oup.com/nar/article/43/1/225/2903413/Identifying-causal-regulatory-SNPs-in-ChIP-seq">
|
||
deSNPs</a> that learn sequence features from a single enhancer-associated chromatin profile and
|
||
consider the k-mer content associated with the genetic variant only,
|
||
<a href="http://www.nature.com/ng/journal/v47/n12/full/ng.3432.html">CATO</a> that predicts chromatin states
|
||
by using high-throughput sequencing data across multiple individuals;
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||
<a href="http://www.nature.com/ng/journal/v46/n3/full/ng.2892.html">C-SCORE</a> that integrates multiple
|
||
annotations into one metric by contrasting variants that survived natural selection with simulated
|
||
mutations; and
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||
<a href="http://nar.oxfordjournals.org/content/early/2016/12/15/nar.gkw1263">CAPE</a> that decomposes the
|
||
sequence code of potential binding sites and the binding sites
|
||
of cofactors from a set of chromatin profiles, and directly quantifies the deactivating effect of a single
|
||
nucleotide mutation based on the corresponding change in the underlying k-mer profile. In our recent study
|
||
published in Nucleic Acids Research, we compared our method CAPE to several other tools and observed
|
||
differential accuracy of the various methods in predicting dsQTLs and eQTLs. The accuracy of causal
|
||
variant prediction varied considerably from no differentiation to >90% depending on a selected method and/or
|
||
a particular cell line. Although, there are methods that generally outperform others, there is no single
|
||
method that performs the best in every scenario.
|
||
</p>
|
||
<p>
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||
SNPDelScore offers pre-compute deleterious effects of noncoding variants using a large panel of currently
|
||
available methods and summarize this information in an interactive, easy to use website. We are also
|
||
providing open access to these data through a RESTfull based web service available through this website.
|
||
Additionally, a Python based web services command line client is available and it can be used to retrieve
|
||
the data from other applications and tools.
|
||
</p>
|
||
</div>
|
||
<h3>GWAS</h3>
|
||
<div>
|
||
<p>
|
||
The GWAS Catalog was downloaded from <a
|
||
href="https://www.ebi.ac.uk/gwas/docs/file-downloads">EBI-GWAS</a>.<br>
|
||
The version included into the database was:
|
||
<a href="ftp://ftp.ncbi.nlm.nih.gov/pub/snpdelscore/GWAS/gwas_catalog_v1.0-associations_e88_r2017-04-03.tsv">
|
||
gwas_catalog_v1.0-associations_e88_r2017-04-03.tsv</a>
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||
</p>
|
||
</div>
|
||
<h3>TFBSs</h3>
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||
<div>
|
||
<p>
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||
The TFBSs were created using the program <a href="https://www.dcode.org/wiki/?n=Main.Programs">tfbsFrag</a>.
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<br>TSV files for each chromosome where created and are available
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||
<a href="ftp://ftp.ncbi.nlm.nih.gov/pub/snpdelscore/TFBS/">here</a>.
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||
</p>
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<p>The TSV file format is:</p>
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||
<pre>
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||
#PWMs START END STRAND SEQUENCE CHROM
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UP00109_1 11456 11470 + ACTGGCGGATTATAG 1
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UP00176_1 11456 11471 + ACTGGCGGATTATAGG 1
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M1053_1.02 11459 11468 - ATAATCCGCC 1
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M5501_1.02 11460 11469 - TATAATCCGC 1
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DMBX1_DBD 11460 11469 + GCGGATTATA 1
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DPRX_DBD_1 11460 11469 + GCGGATTATA 1
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M5346_1.02 11460 11469 - TATAATCCGC 1
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</pre>
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||
<p>An additional
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||
<a href="ftp://ftp.ncbi.nlm.nih.gov/pub/snpdelscore/TFBS/PWMs_mapped_2_humanORmouse.withAlias.withBlast">file</a>
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||
was used to transform PWMs to Gene name.</p>
|
||
</div>
|
||
<h3>Web Services</h3>
|
||
<div>
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<p>The <a href="/research/snpdelscore/api/">web services</a> are available to retrieve the data in JSON or HTML
|
||
formats from a <a href="/research/snpdelscore/static/main/software/snp_rest_client.py" target="_blank">client</a> based in a RESTful service</p>
|
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<h3>RESTful URLs</h3>
|
||
<h4>Retrieve all SNP data</h4>
|
||
<ol>
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||
<li>Search SNP by ID, HTML format:
|
||
<a href="/research/snpdelscore/api/snp/?name=rs7417106">
|
||
https://www.ncbi.nlm.nih.gov/research/snpdelscore/api/snp/?name=rs7417106
|
||
</a>
|
||
</li>
|
||
<li>Search SNP by ID, JSON format:
|
||
<a href="/research/snpdelscore/api/snp.json?name=rs7417106">
|
||
https://www.ncbi.nlm.nih.gov/research/snpdelscore/api/snp/?name=rs7417106&format=json
|
||
</a>
|
||
</li>
|
||
</ol>
|
||
<h4>Retrieve calculated data</h4>
|
||
<ol>
|
||
<li>Search SNP by ID, HTML format:
|
||
<a href="/research/snpdelscore/api/snpdata/?name=rs7417106">
|
||
https://www.ncbi.nlm.nih.gov/research/snpdelscore/api/snpdata/?name=rs7417106
|
||
</a>
|
||
</li>
|
||
<li>Search SNP by ID, JSON format:
|
||
<a href="/research/snpdelscore/api/snpdata.json?name=rs7417106">
|
||
https://www.ncbi.nlm.nih.gov/research/snpdelscore/api/snpdata/?name=rs7417106&format=json
|
||
</a>
|
||
</li>
|
||
<li>Search SNP by Gene name, HTML format:
|
||
<a href="/research/snpdelscore/api/snpdata/?gene_name=DDX11L1">
|
||
https:www.ncbi.nlm.nih.gov/research/snpdelscore/api/snpdata/?gene_name=DDX11L1
|
||
</a>
|
||
</li>
|
||
<li>Search SNP by Gene name, JSON format:
|
||
<a href="/research/snpdelscore/api/snpdata.json?gene_name=DDX11L1">
|
||
https://www.ncbi.nlm.nih.gov/research/snpdelscore/api/snpdata/?gene_name=DDX11L1&format=json
|
||
</a>
|
||
</li>
|
||
<li>Search SNPs by chromosome, HTML format:
|
||
<a href="/research/snpdelscore/api/snpdata/?chr=chr1">
|
||
https://www.ncbi.nlm.nih.gov/research/snpdelscore/api/snpdata/?chr=chr1
|
||
</a>
|
||
</li>
|
||
<li>Search SNPs by chromosome, JSON format:
|
||
<a href="/research/snpdelscore/api/snpdata.json?chr=chr1">
|
||
https://www.ncbi.nlm.nih.gov/research/snpdelscore/api/snpdata/?chr=chr1&format=json
|
||
</a>
|
||
</li>
|
||
<li>Search SNPs by chromosome and region, HTML format:
|
||
<a href="/research/snpdelscore/api/snpdata/?chr=chr1&start=0&end=3369847">
|
||
https://www.ncbi.nlm.nih.gov/research/snpdelscore/api/snpdata/?chr=chr1&start=0&end=3369847
|
||
</a>
|
||
</li>
|
||
<li>Search SNPs by chromosome and region, JSON format:
|
||
<a href="/research/snpdelscore/api/snpdata.json?chr=chr1&start=0&end=3369847">
|
||
https://www.ncbi.nlm.nih.gov/research/snpdelscore/api/snpdata/?chr=chr1&start=0&end=3369847&format=json
|
||
</a>
|
||
</li>
|
||
<li>Search SNPs by method: CAPE eQTL (use method's number as shown in
|
||
<a href="/research/snpdelscore/methods/">Methods</a>),
|
||
HTML format:
|
||
<a href="/research/snpdelscore/api/snpdata/?method=1">
|
||
https://www.ncbi.nlm.nih.gov/research/snpdelscore/api/snpdata/?method=1
|
||
</a>
|
||
</li>
|
||
<li>Search SNPs by method: CAPE eQTL (use method's number as shown in
|
||
<a href="/research/snpdelscore/methods/">Methods</a>),
|
||
JSON format:
|
||
<a href="/research/snpdelscore/api/snpdata.json?method=1">
|
||
https://www.ncbi.nlm.nih.gov/research/snpdelscore/api/snpdata/?method=1&format=json
|
||
</a>
|
||
</li>
|
||
<li>Search SNPs by tissue: GM12878 Lymphoblastoid Cells (use tissue's number as shown in <a
|
||
href="/research/snpdelscore/tissues/">Tissues</a>), HTML format:
|
||
<a href="/research/snpdelscore/api/snpdata/?tissue=33">
|
||
https://www.ncbi.nlm.nih.gov/research/snpdelscore/api/snpdata/?tissue=33
|
||
</a>
|
||
</li>
|
||
<li>Search SNPs by tissue: GM12878 Lymphoblastoid Cells (use tissue's number as shown in <a
|
||
href="/research/snpdelscore/tissues/">Tissues</a>), JSON format:
|
||
<a href="/research/snpdelscore/api/snpdata.json?tissue=33">
|
||
https://www.ncbi.nlm.nih.gov/research/snpdelscore/api/snpdata/?tissue=33&format=json
|
||
</a>
|
||
</li>
|
||
</ol>
|
||
<h3>Results in JSON format</h3>
|
||
<p>The results in JSON format for the calculated data follows the next syntax:</p>
|
||
<pre>
|
||
{
|
||
"count": 4059,
|
||
"next": "https://www.ncbi.nlm.nih.gov/api/snpdata/?page=2",
|
||
"previous": null,
|
||
"results": [
|
||
{
|
||
"name": "rs7417106",
|
||
"pos": 911595,
|
||
"ref": "A",
|
||
"alt": "G",
|
||
"chr": "chr1",
|
||
"method": "CAPE eQTL",
|
||
"tissue": "GM12878 Lymphoblastoid Cells",
|
||
"value": 0.00483957
|
||
]
|
||
}
|
||
</pre>
|
||
<h4>Global Fields</h4>
|
||
<ul>
|
||
<li><b>count</b>: total number of SNPs retrieved</li>
|
||
<li><b>next</b>: URL to be used to retrieve the next set of results</li>
|
||
<li><b>previous</b>: URL to be used to retrieve the previous set of results</li>
|
||
<li><b>results</b>: List of results</li>
|
||
</ul>
|
||
<h4>SNP Fields</h4>
|
||
<ul>
|
||
<li><b>name</b>: SNP ID</li>
|
||
<li><b>pos</b>: SNP position</li>
|
||
<li><b>ref</b>: SNP reference</li>
|
||
<li><b>alt</b>: SNP alternative</li>
|
||
<li><b>chr</b>: Chromosome</li>
|
||
<li><b>method</b>: Method used to calculate the prediction</li>
|
||
<li><b>tissue</b>: Tissue used</li>
|
||
<li><b>value</b>: Prediction value</li>
|
||
</ul>
|
||
<h3>Combining options</h3>
|
||
<p>All options can be used together to retrieve the specific data. For example, to retrieve the list of SNPs in
|
||
the
|
||
region: <b>chr5:5689-758812640</b> calculated with the method <b>CAPE eQTL</b></p>
|
||
<a href="/research/snpdelscore/api/snpdata/?chr=chr5&start=5689&end=758812&&method=1">
|
||
https://www.ncbi.nlm.nih.gov/research/snpdelscore/api/snpdata/?chr=chr5&start=5689&end=758812640&&method=1
|
||
</a>
|
||
</div>
|
||
<h3>Web Services Client</h3>
|
||
<div>
|
||
<p>The Web Services can be accessed through any external application that can query URLs and parse the JSON
|
||
output.</p>
|
||
<h3>Python Client</h3>
|
||
<p>A Python (version 3) script was developed to act as a client for the Web Services. The script can be used to
|
||
query the RESTfull
|
||
API available through this web application.</p>
|
||
<p>The script can be downloaded from <a href="/research/snpdelscore/static/main/software/snp_rest_client.py">here</a> and use
|
||
command line options to retrieve the data.</p>
|
||
<h4>Options used to query the RESTfull API</h4>
|
||
<pre>
|
||
-i Input file. Each line can be snp name, gene name or genome coordinates
|
||
-n Search by SNP ID
|
||
-g Search by Gene name
|
||
-c Search by chromosome name and region. Format: chr1 or chr1:pos or chr1:start-end
|
||
-m Search by method used
|
||
-t Search by tissue used
|
||
-b Print output in BED format
|
||
</pre>
|
||
<h4>Example 1</h4>
|
||
<p>Search SNPs in chromosome 2 calculated with CAPE dsQTL and print the output in BED format.</p>
|
||
<p>Command line:</p>
|
||
<pre>
|
||
#> python snp_rest_client.py -b -m 3 -c chr1:10500-15100
|
||
</pre>
|
||
<p>Output:</p>
|
||
<pre>
|
||
chr1 13116 rs62635286 T G 1.632919 # Method: deltaSVM, Tissue: Average
|
||
chr1 11012 rs544419019 C G 1.357423 # Method: deltaSVM, Tissue: Average
|
||
chr1 11012 rs544419019 C G 3.137345 # Method: deltaSVM, Tissue: GM12878 Lymphoblastoid Cells
|
||
chr1 13116 rs62635286 T G 0.324705 # Method: deltaSVM, Tissue: GM12878 Lymphoblastoid Cells
|
||
chr1 13118 rs200579949 A G 1.696014 # Method: deltaSVM, Tissue: Average
|
||
chr1 13118 rs200579949 A G 1.195338 # Method: deltaSVM, Tissue: GM12878 Lymphoblastoid Cells
|
||
chr1 13273 rs531730856 G C 0.909246 # Method: deltaSVM, Tissue: GM12878 Lymphoblastoid Cells
|
||
...
|
||
</pre>
|
||
<h4>Example 2</h4>
|
||
<p>Search SNPs from file and print the output in BED format.</p>
|
||
<p>Command line:</p>
|
||
<pre>
|
||
#> python snp_rest_client.py -b -i infile
|
||
</pre>
|
||
<p>Input file: infile</p>
|
||
<pre>
|
||
rs62635286
|
||
chr1:11000-11100
|
||
</pre>
|
||
<p>Output:</p>
|
||
<pre>
|
||
chr1 13116 rs62635286 T G 0.324705 # Method: deltaSVM, Tissue: GM12878 Lymphoblastoid Cells
|
||
chr1 13116 rs62635286 T G 2.54928 # Method: deltaSVM, Tissue: HepG2 Hepatocellular Carcinoma
|
||
chr1 13116 rs62635286 T G 2.024774 # Method: deltaSVM, Tissue: K562 Leukemia Cells
|
||
chr1 11012 rs544419019 C G 3.137345 # Method: deltaSVM, Tissue: GM12878 Lymphoblastoid Cells
|
||
chr1 11012 rs544419019 C G 0.599368 # Method: deltaSVM, Tissue: HepG2 Hepatocellular Carcinoma
|
||
chr1 11012 rs544419019 C G 0.335556 # Method: deltaSVM, Tissue: K562 Leukemia Cells
|
||
</pre>
|
||
<h4>Example 3</h4>
|
||
<p>Search SNPs from file with data calculated for the tissue: K562 Leukemia Cells and print the output in BED
|
||
format.</p>
|
||
<p>Command line:</p>
|
||
<pre>
|
||
#> python snp_rest_client.py -b -i infile -t 40
|
||
</pre>
|
||
<p>Input file: infile</p>
|
||
<pre>
|
||
rs62635286
|
||
chr1:11000-11100
|
||
</pre>
|
||
<p>Output:</p>
|
||
<pre>
|
||
chr1 13116 rs62635286 T G 2.024774 # Method: deltaSVM, Tissue: K562 Leukemia Cells
|
||
chr1 11012 rs544419019 C G 0.335556 # Method: deltaSVM, Tissue: K562 Leukemia Cells
|
||
</pre>
|
||
</div>
|
||
<h3>How to include data into the SNPDelScore database?</h3>
|
||
<div>
|
||
<p>SNPDelScore is based on a set of SNPs IDs. Download this
|
||
<a href="ftp://ftp.ncbi.nlm.nih.gov/pub/snpdelscore/SNPs/SNPs.vcf.gz">VCF file</a> for a complete
|
||
list of available SNPs
|
||
(<a href="https://samtools.github.io/hts-specs/VCFv4.2.pdf">VCF format definition</a>).
|
||
Currently, SNPDelScore includes 12 591 046 SNPs.
|
||
</p>
|
||
<pre>
|
||
#CHROM POS ID REF ALT
|
||
chr1 11008 rs575272151 C G
|
||
chr1 11012 rs544419019 C G
|
||
chr1 13110 rs540538026 G A
|
||
chr1 13116 rs62635286 T G
|
||
chr1 13118 rs200579949 A G
|
||
chr1 13273 rs531730856 G C
|
||
chr1 14464 rs546169444 A T
|
||
</pre>
|
||
<p>SNPDelScore is able to import data in the same format including any predicted value as an extra column.
|
||
Please, note that it should be submitted <b>one file per cell line</b> using the method name and the tissue
|
||
code in the file name, e.g.
|
||
<a href="ftp://ftp.ncbi.nlm.nih.gov/pub/snpdelscore/rawdata/CAPE_dsQTL_E003.vcf.gz">
|
||
CAPE_dsQTL_E003.vcf.gz</a> for method CAPE-dsQTL and the cell line H1 Cells (E003).
|
||
</p>
|
||
<p>Check our raw data files <a href="/research/snpdelscore/rawdata/">here</a></p>
|
||
<p>Contact <a href="mailto:ovcharen@nih.gov">Dr. Ivan Ovcharenko</a> for data submission.</p>
|
||
<pre>
|
||
#CHROM POS ID REF ALT VALUE
|
||
chr1 11008 rs575272151 C G 0.9942
|
||
chr1 13110 rs540538026 G A 0.0386
|
||
chr1 14930 rs75454623 A G 0.0685
|
||
chr1 15211 rs78601809 T G 0.2551
|
||
chr1 16949 rs199745162 A C 0.0261
|
||
chr1 30923 rs806731 G T 0.0857
|
||
</pre>
|
||
</div>
|
||
<h3>Contacts</h3>
|
||
<div>
|
||
<p>Any question, comment or request should be addressed to
|
||
<a href="mailto:ovcharen@nih.gov">Dr. Ivan Ovcharenko</a>
|
||
</p>
|
||
<h4>Collaborators</h4>
|
||
<ul>
|
||
<li><a href="mailto:veraalva@ncbi.nlm.nih.gov">Dr. Roberto Vera Alvarez</a></li>
|
||
<li><a href="mailto:shan.li@nih.gov">Dr. Shan Li</a></li>
|
||
<li><a href="mailto:landsman@ncbi.nlm.nih.gov">Dr. David Landsman</a></li>
|
||
</ul>
|
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</div>
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</div>
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