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Template:Novel motif: Difference between revisions

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mNo edit summary
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     $('#h_pval_table').DataTable({
     $('#h_pval_table').DataTable({
dom: 'lfrtip',
dom: 'Blfrtip',
buttons: ['copyHtml5', 'excelHtml5', 'csvHtml5', 'pdfHtml5'],
scrollY: "300px",
scrollY: "300px",
scrollCollapse: true,
scrollCollapse: true,
pLength: 10,
searching: true,
        pageLength: 10,
lengthMenu: [[5,10,-1], [5,10,"All"]],
lengthMenu: [[5,10,-1], [5,10,"All"]],
data: h_data,
data: h_data,
Line 44: Line 46:
           { targets: 1, width: "50pt"}
           { targets: 1, width: "50pt"}
         ],
         ],
columns: [{ title: "FF samples", render: function(data, type, row, meta) {
columns: [
return '<a href="/5/sstar/index.php/FF:'+row[ 0 ].split('.').pop()+'">'+decodeURIComponent(row[ 0 ])+'</a>';
{ title: "FF samples", 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];
{ title: "p-value",  type: "numeric", render: function (data, type, row, meta) {                     
          return exp_converter(num,2,"e") ;
        var num = row[1];
} }],
          return exp_converter(num,2,"e") ;
} }
],
order: [[ 1, "asc" ]],
order: [[ 1, "asc" ]],
});
});




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$('#m_pval_table').DataTable({
$('#m_pval_table').DataTable({
dom: 'lfrtip',
dom: 'Blfrtip',
buttons: ['copyHtml5', 'excelHtml5', 'csvHtml5', 'pdfHtml5'],
scrollY: "300px",
scrollY: "300px",
scrollCollapse: true,
scrollCollapse: true,
Line 76: Line 81:
],
],
columns: [
columns: [
{ title: "FF samples",  orderable: false, render: function(data, type, row, meta) {
{ title: "FF samples", render: function(data, type, row, meta) {
return '<a href="/5/sstar/index.php/FF:'+row[0].split('.').pop()+'">'+decodeURIComponent(row[ 0 ])+'</a>';
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) {                     
{ title: "p-value",  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") ;
Line 88: Line 93:
order: [[ 1, "asc" ]],
order: [[ 1, "asc" ]],
});
});


// GREAT table for human start
// GREAT table for human start

Revision as of 14:09, 17 January 2020

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 IDGO Termp-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 IDGO Termp-value
{{{great_results_mouse}}}