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{{Loading|loadingimage=sprites.gif}}<html>
{{Loading|loadingimage=sprites.gif}}<html>
<style type="text/css" title="currentStyle">
<style type="text/css" title="currentStyle">
@import "/resource_browser/rb_js/datatables/media/css/jquery.dataTables.css";
@import "/5/sstar/rb_js/html5button/datatables.css";
@import "/resource_browser/rb_js/datatables/extras/TableTools/media/css/TableTools.css";
@import "/5/sstar/rb_js/datatables/extras/TableTools/media/css/TableTools.css";
 
.content, .sidebar
.content, .sidebar
{
{
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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" language="javascript" src="/5/sstar/rb_js/jquery-1.7.1.min.js"></script>
<script type="text/javascript" src="/5/sstar/rb_js/html5button/datatables.js"></script>
<script type="text/javascript" src="/resource_browser/rb_js/custom/convert.js"></script>
<script type="text/javascript" src="/5/sstar/rb_js/custom/convert.js"></script>
<script type="text/javascript" src="/resource_browser/rb_js/datatables/media/js/jquery.dataTables.min.js"></script>
<script type="text/javascript" language="javascript" src="/resource_browser/rb_js/datatables/extras/TableTools/media/js/ZeroClipboard.js"></script>
<script type="text/javascript" language="javascript" src="/resource_browser/rb_js/datatables/extras/TableTools/media/js/TableTools.js">
</script>
</script>
<script type="text/javascript">
<script type="text/javascript">
$(document).ready(function() {
$(document).ready(function() {
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}
}


     $('#h_pval_table').dataTable({
     $('#h_pval_table').DataTable({
"sScrollY": "300px",
dom: 'lfrtip',
"bScrollCollapse": true,
scrollY: "300px",
"bPaginate": true,
scrollCollapse: true,
"bFilter": true,
pageLength: 10,
"bInfo": true,
lengthMenu: [[5,10,-1], [5,10,"All"]],
                "iDisplayLength": 10,
data: h_data,
                "aLengthMenu": [[5,10,-1], [5,10,"All"]],
columns: [
"aaData": h_data,
{ "title": "FF samples", "orderable": false, render: function(data, type, row, meta) {
"aoColumns": [{ "sTitle": "FF samples", "bSortable": false, "fnRender": function(obj) {
return '<a href="/5/sstar/index.php/FF:'+row[ 0 ].split('.').pop()+'">'+decodeURIComponent(row[ 0 ])+'</a>';
return sReturn = '<a href="/resource_browser/index.php/FF:'+obj.aData[ obj.iDataColumn ].split('.').pop()+'">'+decodeURIComponent(obj.aData[ obj.iDataColumn ])+'</a>';
} },
} },{ "sTitle": "p-value",  "sType": "numeric", "sWidth": "50pt" , "aTargets": [1],"fnRender": function (obj) {                     
{ title: "p-value",  type: "numeric", "width": "50pt", render: function (data, type, row, meta) {                     
                  var num =obj.aData[obj.iDataColumn];
        var num = row[1];
                  return exp_converter(num,2,"e") ;
          return exp_converter(num,2,"e");
} }],
} }
"aaSorting": [[ 1, "asc" ]],
],
order: [[ 1, "asc" ]],
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}
}


    var oTable = $('#m_pval_table').dataTable({
$('#m_pval_table').DataTable({
"sScrollY": "300px",
dom: 'lfrtip',
"bScrollCollapse": true,
scrollY: "300px",
"bPaginate": true,
scrollCollapse: true,
"bFilter": true,
    pageLength: 10,
"bInfo": true,
lengthMenu: [[5,10,-1], [5,10,"All"]],
                "iDisplayLength": 10,
data: m_data,
                "aLengthMenu": [[5,10,-1], [5,10,"All"]],
columns: [
"aaData": m_data,
{ title: "FF samples", "orderable": false, render: function(data, type, row, meta) {
"aoColumns": [{ "sTitle": "FF samples", "bSortable": false, "fnRender": function(obj) {
return '<a href="/5/sstar/index.php/FF:'+row[0].split('.').pop()+'">'+decodeURIComponent(row[ 0 ])+'</a>';
return sReturn = '<a href="/resource_browser/index.php/FF:'+obj.aData[ obj.iDataColumn ].split('.').pop()+'">'+decodeURIComponent(obj.aData[ obj.iDataColumn ])+'</a>';
}
} },{ "sTitle": "p-value", "sType": "numeric", "sWidth": "50pt", "aTargets": [1],"fnRender": function (obj) {                     
},
                  var num =obj.aData[obj.iDataColumn];
{ title: "p-value", width: "50pt", type: "numeric", render: function (data, type, row, meta) {                     
                  return exp_converter(num,2,"e") ;
              var num =row[1];
} }],
              return exp_converter(num,2,"e");
"aaSorting": [[ 1, "asc" ]],
}
}
],
order: [[ 1, "asc" ]],
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var oTableTools = new TableTools( oTable, {"sSwfPath": "/resource_browser/rb_js/datatables/extras/TableTools/media/swf/copy_csv_xls_pdf.swf", "aButtons": [ {"sExtends": "copy", "mColumns": "visible"}, {"sExtends": "csv", "mColumns": "visible"}, {"sExtends": "pdf", "mColumns": "visible"} ]});
$('#export_tool').before( oTableTools.dom.container );


// GREAT table for human start
// GREAT table for human start
$('#great_table_human').dataTable({
$('#great_table_human').DataTable({
"sScrollY": "300px",
dom:'lfrtip',
"bScrollCollapse": true,
scrollY:"300px",
"bPaginate": true,
scrollCollapse:true,
"bFilter": true,
    pageLength:10,
"bInfo": true,
    lengthMenu:[[5,10,-1], [5,10,"All"]],
                "iDisplayLength": 10,
order:[[ 2, "asc" ]],
                "aLengthMenu": [[5,10,-1], [5,10,"All"]],
columns:[
"aaSorting": [[ 2, "asc" ]],
{"orderable":false},
"aoColumnDefs": [{ "bSortable": false, "aTargets": [0,1] },{ "sType": "numeric", "sWidth": "80pt", "aTargets": [2],"fnRender": function (obj) {                  
{"orderable":false},
                  var num =obj.aData[obj.iDataColumn];
{type: "html-number", width: "80pt", render: function(data, type, row, meta) {
                  return exp_converter(num,2,"e") ;
              var num =row[2];
} }]
              return exp_converter(num,2,"e");
}
}
]
});
});
// GREAT table for human end
// GREAT table for human end


// GREAT table for mouse start
// GREAT table for mouse start
$('#great_table_mouse').dataTable({
$('#great_table_mouse').DataTable({
"sScrollY": "300px",
dom: 'lfrtip',
"bScrollCollapse": true,
scrollY: "300px",
"bPaginate": true,
scrollCollapse: true,
"bFilter": true,
    pageLength: 10,
"bInfo": true,
    lengthMenu: [[5,10,-1], [5,10,"All"]],
                "iDisplayLength": 10,
order: [[ 2, "asc" ]],
                "aLengthMenu": [[5,10,-1], [5,10,"All"]],
columns: [
"aaSorting": [[ 2, "asc" ]],
{"orderable": false},
"aoColumnDefs": [{ "bSortable": false, "aTargets": [0,1] },{ "sType": "numeric", "sWidth": "80pt", "aTargets": [2], "fnRender": function (obj) {                  
{"orderable": false},
                  var num =obj.aData[obj.iDataColumn];
{type: "html-number", width: "80pt", render: function(data, type, row, meta) {
                  return exp_converter(num,2,"e") ;
              var num =row[2];
} }]
              return exp_converter(num,2,"e");
}
}
]
});
});
// GREAT table for mouse end
// GREAT table for mouse end
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     </div>
     </div>
   <div class="content">
   <div class="content">
         <img src="/resource_browser/seqlogos/novel/</html>{{PAGENAME}}<html>.png">
         <img src="/5/sstar/seqlogos/novel/</html>{{PAGENAME}}<html>.png">
   </div>
   </div>
  </div></html>
  </div></html>
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<br><br>
<br><br>
link to source dataset <br>
link to source dataset <br>
[http://fantom.gsc.riken.jp/5/datafiles/phase1.1/extra/Motifs/novel_Significance_of_the_correlation_with_CAGE_expression/hg19.pvalues.txt data]
[//fantom.gsc.riken.jp/5/datafiles/phase1.1/extra/Motifs/novel_Significance_of_the_correlation_with_CAGE_expression/hg19.pvalues.txt data]
}}
}}
----
----
<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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<br><br>
<br><br>
link to source dataset <br>
link to source dataset <br>
[http://fantom.gsc.riken.jp/5/datafiles/phase1.1/extra/Motifs/novel_Significance_of_the_correlation_with_CAGE_expression/mm9.pvalues.txt data]
[//fantom.gsc.riken.jp/5/datafiles/phase1.1/extra/Motifs/novel_Significance_of_the_correlation_with_CAGE_expression/mm9.pvalues.txt data]
}}
}}
----
----
<!--
<table id="m_pval_table" class="ff_sample_list stripe cell-border order-column compact dataTable no-footer"></table>
<span id="export_tool"></span>
-->
<table id="m_pval_table"></table>
<br><br>
<br><br>
{{Fontsize|3|GREAT analysis results for human}}
{{Fontsize|3|GREAT analysis results for human}}
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<br><br>
<br><br>
link to source dataset <br>
link to source dataset <br>
[http://fantom.gsc.riken.jp/5/datafiles/phase1.1/extra/Motifs/novel_GREAT_analysis_results/hg19.table.txt data]
[//fantom.gsc.riken.jp/5/datafiles/phase1.1/extra/Motifs/novel_GREAT_analysis_results/hg19.table.txt data]
}}
}}
----
----
<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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{{Fontsize|3|GREAT analysis results for mouse}}{{#info: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>
{{Fontsize|3|GREAT analysis results for mouse}}{{#info: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>
link to source dataset <br>
[http://fantom.gsc.riken.jp/5/datafiles/phase1.1/extra/Motifs/novel_GREAT_analysis_results/mm9.table.txt data]
[//fantom.gsc.riken.jp/5/datafiles/phase1.1/extra/Motifs/novel_GREAT_analysis_results/mm9.table.txt data]
}}
}}
----
----
{{#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




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