Template:Novel motif: Difference between revisions
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table.details th { width:10%; background-color: #5A5FB5; color: white;} | table.details th { width:10%; background-color: #5A5FB5; color: white;} | ||
</style> | </style> | ||
<script type="text/javascript" src="/5/sstar/rb_js/html5button/datatables.js"></script> | <script type="text/javascript" src="/5/sstar/rb_js/html5button/datatables.js"></script> | ||
<script type="text/javascript" src="/5/sstar/rb_js/custom/convert.js"></script> | <script type="text/javascript" src="/5/sstar/rb_js/custom/convert.js"></script> | ||
</script> | |||
<script type="text/javascript"> | <script type="text/javascript"> | ||
$(document).ready(function() { | $(document).ready(function() { | ||
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scrollY: "300px", | scrollY: "300px", | ||
scrollCollapse: true, | scrollCollapse: true, | ||
pageLength: 10, | |||
lengthMenu: [[5,10,-1], [5,10,"All"]], | lengthMenu: [[5,10,-1], [5,10,"All"]], | ||
data: h_data, | data: h_data, | ||
columns: [ | |||
{ "title": "FF samples", "orderable": false, render: function(data, type, row, meta) { | |||
return '<a href="/5/sstar/index.php/FF:'+row[ 0 ].split('.').pop()+'">'+decodeURIComponent(row[ 0 ])+'</a>'; | |||
} }, | |||
{ title: "p-value", type: "numeric", "width": "50pt", render: function (data, type, row, meta) { | |||
var num = row[1]; | |||
return exp_converter(num,2,"e"); | |||
} } | |||
], | |||
order: [[ 1, "asc" ]], | order: [[ 1, "asc" ]], | ||
}); | |||
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scrollY: "300px", | scrollY: "300px", | ||
scrollCollapse: true, | scrollCollapse: true, | ||
pageLength: 10, | |||
lengthMenu: [[5,10,-1], [5,10,"All"]], | lengthMenu: [[5,10,-1], [5,10,"All"]], | ||
data: m_data, | data: m_data, | ||
columns: [ | columns: [ | ||
{ title: "FF samples", | { title: "FF samples", "orderable": false, render: function(data, type, row, meta) { | ||
return '<a href="/ | return '<a href="/5/sstar/index.php/FF:'+row[0].split('.').pop()+'">'+decodeURIComponent(row[ 0 ])+'</a>'; | ||
} | } | ||
}, | }, | ||
{ title: "p-value", | { title: "p-value", width: "50pt", type: "numeric", render: function (data, type, row, meta) { | ||
var num =row[1]; | var num =row[1]; | ||
return exp_converter(num,2,"e") ; | return exp_converter(num,2,"e"); | ||
} | } | ||
} | } | ||
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order: [[ 1, "asc" ]], | order: [[ 1, "asc" ]], | ||
}); | }); | ||
// GREAT table for human start | // GREAT table for human start | ||
$('#great_table_human').DataTable({ | $('#great_table_human').DataTable({ | ||
dom: 'lfrtip', | dom:'lfrtip', | ||
scrollY: "300px", | scrollY:"300px", | ||
scrollCollapse: true, | scrollCollapse:true, | ||
pageLength:10, | |||
lengthMenu: [[5,10,-1], [5,10,"All"]], | lengthMenu:[[5,10,-1], [5,10,"All"]], | ||
order: [[ 2, "asc" ]], | order:[[ 2, "asc" ]], | ||
columns:[ | |||
{ | {"orderable":false}, | ||
{ | {"orderable":false}, | ||
{ | {type: "html-number", width: "80pt", render: function(data, type, row, meta) { | ||
var num =row[2]; | |||
return exp_converter(num,2,"e"); | |||
var num =row[ | |||
return exp_converter(num,2,"e") ; | |||
} | } | ||
} | } | ||
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// GREAT table for mouse start | // GREAT table for mouse start | ||
$('#great_table_mouse').DataTable({ | $('#great_table_mouse').DataTable({ | ||
dom: 'lfrtip', | |||
scrollY: "300px", | scrollY: "300px", | ||
scrollCollapse: true, | scrollCollapse: true, | ||
pageLength: 10, | |||
lengthMenu: [[5,10,-1], [5,10,"All"]], | lengthMenu: [[5,10,-1], [5,10,"All"]], | ||
order: [[ 2, "asc" ]], | order: [[ 2, "asc" ]], | ||
columns: [ | columns: [ | ||
{ | {"orderable": false}, | ||
{ | {"orderable": false}, | ||
{ | {type: "html-number", width: "80pt", render: function(data, type, row, meta) { | ||
var num =row[ | var num =row[2]; | ||
return exp_converter(num,2,"e") ; | return exp_converter(num,2,"e"); | ||
} | } | ||
} | } | ||
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</div> | </div> | ||
<div class="content"> | <div class="content"> | ||
<img src="/ | <img src="/5/sstar/seqlogos/novel/</html>{{PAGENAME}}<html>.png"> | ||
</div> | </div> | ||
</div></html> | </div></html> | ||
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}} | }} | ||
---- | ---- | ||
<table id="h_pval_table"></table> | <table id="h_pval_table" class="ff_sample_list stripe cell-border order-column compact dataTable no-footer"></table> | ||
<br><br> | <br><br> | ||
{{Fontsize|3|Association to promoter expression in mouse samples}} | {{Fontsize|3|Association to promoter expression in mouse samples}} | ||
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}} | }} | ||
---- | ---- | ||
< | <table id="m_pval_table" class="ff_sample_list stripe cell-border order-column compact dataTable no-footer"></table> | ||
-- | |||
<br><br> | <br><br> | ||
{{Fontsize|3|GREAT analysis results for human}} | {{Fontsize|3|GREAT analysis results for human}} | ||
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}} | }} | ||
---- | ---- | ||
<table id="great_table_human"> | <table id="great_table_human" class="ff_sample_list stripe cell-border order-column compact dataTable no-footer"> | ||
<html><thead></html> | <html><thead></html> | ||
<th>GO ID</th><th>GO Term</th><th>p-value</th> | <th>GO ID</th><th>GO Term</th><th>p-value</th> | ||
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---- | ---- | ||
{{#if:{{{great_results_mouse}}}| | {{#if:{{{great_results_mouse}}}| | ||
<table id="great_table_mouse"> | <table id="great_table_mouse" class="ff_sample_list stripe cell-border order-column compact dataTable no-footer"> | ||
<html><thead></html> | <html><thead></html> | ||
<th>GO ID</th><th>GO Term</th><th>p-value</th>{{#arraydefine:tmp_go_stat_mouse|{{{great_results_mouse}}}|!}} | <th>GO ID</th><th>GO Term</th><th>p-value</th>{{#arraydefine:tmp_go_stat_mouse|{{{great_results_mouse}}}|!}} |
Latest revision as of 16:22, 24 September 2021
name: | {{{name}}} |
---|
Association to promoter expression in human samples<b>Summary:</b>Significance of the correlation with CAGE expression, human <br><b>Analyst:</b> Michiel de Hoon<br><br>link to source dataset <br>data
Association to promoter expression in mouse samples
<b>Summary:</b>Significance of the correlation with CAGE expression, mouse <br><b>Analyst:</b> Michiel de Hoon<br><br>link to source dataset <br>data
GREAT analysis results for human
<b>Summary:</b>Genomic Enrichment of Annotations Tool (GREAT, Nat Biotechnol. 2010 May;28(5):495-501) is used to identify, both in human and in mouse, the gene ontology terms of biological processes enriched given the predicted TFBSs, and evaluated the overlap in the top-500 gene ontology terms between human and mouse. For each novel motif, the P value for the overlap was then evaluated by calculating its relative rank with respect to this background distribution.<br>Analyst: Michiel de Hoon<br><br>link to source dataset <br>data
GO ID | GO Term | p-value |
---|---|---|
{{{great_results_human}}} |
GREAT analysis results for mouseGenomic Enrichment of Annotations Tool (GREAT, Nat Biotechnol. 2010 May;28(5):495-501) is used to identify, both in human and in mouse, the gene ontology terms of biological processes enriched given the predicted TFBSs, and evaluated the overlap in the top-500 gene ontology terms between human and mouse. For each novel motif, the P value for the overlap was then evaluated by calculating its relative rank with respect to this background distribution.<br>Analyst: Michiel de Hoon <br><br>link to source dataset <br>data
GO ID | GO Term | p-value |
---|---|---|
{{{great_results_mouse}}} |