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lung_CL_phos_ratios_Y.html
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lung_CL_phos_ratios_Y.html
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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="">
<meta name="author" content="">
<!-- <base href='/clustergrammer/'> -->
<title>Clustergrammer</title>
<link rel="shortcut icon" href="static/icons/graham_cracker.ico" type="image/x-icon">
<link rel="stylesheet" href="lib/css/bootstrap.css">
<link rel="stylesheet" href="lib/css/jquery-ui.css">
<link rel="stylesheet" href="lib/font-awesome.min.css">
<link rel="stylesheet" href="css/custom_multiple_clust.css">
<style>
#input_form {display: none}
</style>
</head>
<body>
<div id="wrap" class='toggled container'>
<div class='row viz_title' id='clustergram_title'>
<!-- Clustergrammer -->
<!-- <img id='clustergrammer_logo' src='img/clustergrammer_logo.png'> -->
<h2>Lung Cell Line Tyrosine Phosphorylation</h2>
</div>
<div class="row" >
<div id='container-id-1' class='clustergrammer_container'>
<div class='wait_message'>Please wait ...</div>
</div>
</div>
<div class='row viz_description' id='clustergram_desc'>
<p>Above is a clustergram/heatmap visualization of your input matrix. The rows and columns have been hierarchically clustered, using the Scipy library in Python, using cosine distance and average linkage. Red/blue cells in the matrix represent positive/negative values in your matrix. The visualization interactive (zoomable, reorderable, filterable) and shareable - the current URL is permanent and shareable.</p>
</div>
<div class='row viz_title' id='col_sim_title'>
Column Similarity Matrix
</div>
<div class="row" >
<div id='container-id-2' class='clustergrammer_container sim_mat_container'>
<div class='wait_message'>Please wait ...</div>
</div>
</div>
<div class='row viz_description' id='col_sim_desc'>
<p>Above is a similarity matrix of the columns in your input matrix. The cells in the matrix represent the similarity between columns, where red/blue represent positive/negative similarity (measured as 1 - cosine-distance). Similarity matrices offer a more detailed view of the similarities and differences between rows/columms, e.g. blue cells indicate data points that behave 'oppositely' and this can not be easily seen in a clustergram/heatmap view.</p>
</div>
<div class='row viz_title' id='row_sim_title'>
Row Similarity Matrix
</div>
<div class="row" >
<div id='container-id-3' class='clustergrammer_container sim_mat_container'>
<div class='wait_message'>Please wait ...</div>
</div>
</div>
<div class='row viz_description' id='row_sim_desc'>
<p>Above is a similarity matrix of the rows in your input matrix. The cells in the matrix represent the similarity between rows, where red/blue represent positive/negative similarity (measured as 1 - cosine-distance). </p>
</div>
</div>
<div id='footer'>
<div class="row" >
<div id='footer_text_container' class="col-xs-12 footer_section">
<div class="text-muted footer_text">Clustergrammer is being developed by the <a class='blue_links' target="_blank" href="http://icahn.mssm.edu/research/labs/maayan-laboratory">Ma'ayan Lab</a> at the <a class='blue_links' target="_blank" href="http://icahn.mssm.edu/">Icahn School of Medicine at Mount Sinai</a> for the <a target="_blank" href="http://lincs-dcic.org/">BD2K-LINCS DCIC</a> and the <a target="_blank" href="http://commonfund.nih.gov/idg/overview">KMC-IDG</a> </div>
<!-- DCIC, BD2K, KMC, and GitHub -->
<div class="text-muted footer_text">
and is an open source project available on GitHub: <a class='blue_links' target="_blank" href="https://github.com/MaayanLab/clustergrammer">Clustergrammer</a> and <a class='blue_links' target="_blank" href="https://github.com/cornhundred/clustergrammer.js">Clustergrammer.js</a>
</div>
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</div>
</div>
<!-- Required JS Libraries -->
<script src="lib/js/d3.js"></script>
<script src="lib/js/jquery-1.11.2.min.js"></script>
<script src="lib/js/jquery-ui.js"></script>
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<script src="lib/js/blockUI.js"></script>
<!-- Clustergrammer JS -->
<script src='js/clustergrammer.js'></script>
<script src='js/load_multiple_clustergrams.js'></script>
<script type="text/javascript">
load_viz_data('lung_CL_phos_ratios_Y');
</script>
</body>