Mercurial > repos > rnateam > rbpbench

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author rnateam
date Sun, 03 Dec 2023 12:51:54 +0000
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7dd2835ce566 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/rna_tools/rbpbench commit 0e21bd630200c1f199db8ba5d83b81d4214fc59f
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1 <p><head>
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2 <title>RBPBench - Search Report</title></p>
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3 <script src="/home/uhlm/Programme/miniconda3/envs/rbpbench/lib/python3.11/site-packages/rbpbench/content/sorttable.js" type="text/javascript"></script>
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4 <p></head></p>
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5 <h1>Search report</h1>
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6 <p>List of available statistics and plots generated
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7 by RBPBench (rbpbench search --report):</p>
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8 <ul>
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9 <li><a href="#rbp-enrich-stats">RBP motif enrichment statistics</a></li>
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10 <li><a href="#cooc-heat-map">RBP co-occurrences heat map</a></li>
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11 <li><a href="#corr-heat-map">RBP correlations heat map</a>
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12 &nbsp;</li>
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13 </ul>
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14 <h2 id="rbp-enrich-stats">RBP motif enrichment statistics</h2>
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15 <p><strong>Table:</strong> RBP motif enrichment statistics. Given a score for each genomic region (# input regions = 1),
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16 RBPbench checks whether motifs are enriched
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17 in higher-scoring regions (using Wilcoxon rank-sum test). A low Wilcoxon rank-sum test p-value for a given RBP thus indicates
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18 that higher-scoring regions are more likely to contain motif hits of the respective RBP. NOTE that if scores associated to
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19 input genomic regions are all the same, p-values become meaningless (i.e., they result in p-values of 1.0).</p>
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20 <table class="sortable">
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21 <thead>
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22 <tr>
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23 <th style="text-align: center;">RBP ID</th>
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24 <th style="text-align: center;"># hit regions</th>
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25 <th style="text-align: center;">% hit regions</th>
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26 <th style="text-align: center;"># motif hits</th>
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27 <th style="text-align: center;">p-value</th>
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28 </tr>
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29 </thead>
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30 <tbody>
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31 <tr>
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32 <td style="text-align: center;">PUM1</td>
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33 <td style="text-align: center;">1</td>
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34 <td style="text-align: center;">100.00</td>
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35 <td style="text-align: center;">1</td>
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36 <td style="text-align: center;">1.0</td>
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37 </tr>
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38 <tr>
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39 <td style="text-align: center;">PUM2</td>
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40 <td style="text-align: center;">1</td>
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41 <td style="text-align: center;">100.00</td>
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42 <td style="text-align: center;">4</td>
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43 <td style="text-align: center;">1.0</td>
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44 </tr>
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45 </tbody>
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46 </table>
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47 <p>&nbsp;
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48 &nbsp;</p>
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49 <p>Column IDs have the following meanings: <strong>RBP ID</strong> -&gt; RBP ID from database or user-defined (typically RBP name), <strong># hit regions</strong> -&gt; number of input genomic regions with motif hits (after filtering and optional extension), <strong>% hit regions</strong> -&gt; percentage of hit regions over all regions (i.e. how many input regions contain &gt;= 1 RBP binding motif), <strong># motif hits</strong> -&gt; number of unique motif hits in input regions (removed double counts), <strong>p-value</strong> -&gt; Wilcoxon rank-sum test p-value.</p>
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50 <h2 id="cooc-heat-map">RBP co-occurrences heat map</h2>
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51 <p>RBP co-occurrences heat map.</p>
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52 <div class=class="container-fluid" style="margin-top:40px">
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53 <iframe src="html_report_plots/co-occurrence_plot.plotly.html" width="1200" height="1200"></iframe>
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54 </div>
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55
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56 <p><strong>Figure:</strong> Heat map of co-occurrences (Fisher's exact test p-values) between RBPs.
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57 Legend color: negative logarithm (base 10) of Fisher's exact test p-value.
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58 Hover box: 1) RBP1. 2) RBP2. 3) p-value: Fisher's exact test p-value (calculated based on contingency table between RBP1 and RBP2).
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59 4) RBPs compaired. 5) Counts[]: Contingency table of co-occurrence counts (i.e., number of genomic regions with/without shared motif hits) between compaired RBPs,
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60 with format [[A, B], [C, D]], where
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61 A: RBP1 AND RBP2,
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62 B: NOT RBP1 AND RBP2
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63 C: RBP1 AND NOT RBP2
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64 D: NOT RBP1 AND NOT RBP2. </p>
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65 <p>&nbsp;</p>
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66 <h2 id="corr-heat-map">RBP correlations heat map</h2>
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67 <p>RBP correlations heat map.</p>
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68 <div class=class="container-fluid" style="margin-top:40px">
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69 <iframe src="html_report_plots/correlation_plot.plotly.html" width="1200" height="1200"></iframe>
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70 </div>
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71
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72 <p><strong>Figure:</strong> Heat map of correlations (Pearson correlation coefficients) between RBPs.
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73 Genomic regions are labelled 1 or 0 (RBP motif present or not), resulting in a vector of 1s and 0s for each RBP.
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74 Correlations are then calculated by comparing vectors for every pair of RBPs.
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75 Legend color: Pearson correlation coefficient.
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76 Hover box: 1) RBP1. 2) RBP2.
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77 3) RBPs compaired. 5) Counts[]: Contingency table of co-occurrence counts (i.e., number of genomic regions with/without shared motif hits) between compaired RBPs,
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78 with format [[A, B], [C, D]], where
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79 A: RBP1 AND RBP2,
7dd2835ce566 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/rna_tools/rbpbench commit 0e21bd630200c1f199db8ba5d83b81d4214fc59f
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80 B: NOT RBP1 AND RBP2
7dd2835ce566 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/rna_tools/rbpbench commit 0e21bd630200c1f199db8ba5d83b81d4214fc59f
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81 C: RBP1 AND NOT RBP2
7dd2835ce566 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/rna_tools/rbpbench commit 0e21bd630200c1f199db8ba5d83b81d4214fc59f
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82 D: NOT RBP1 AND NOT RBP2. </p>
7dd2835ce566 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/rna_tools/rbpbench commit 0e21bd630200c1f199db8ba5d83b81d4214fc59f
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83 <p>&nbsp;</p>