Commit e9ce3f7d authored by magali's avatar magali
Browse files

dernières modifs rmd

parent 4693af63
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......@@ -48,7 +48,7 @@ options(DT.options = list(pageLength = 10,
- Adresse du dépot: git@forgemia.inra.fr:magali.monnoye/analyses_16s.git
- Repository sur la plateforme migale: <strong class="tool">ssh -X mmonnoye@migale.jouy.inrae.fr</strong> dans save/analyses_16S/202111_Rotenone/
- Repository sur la plateforme migale: <strong class="tool">ssh -X mmonnoye@migale.jouy.inrae.fr</strong> dans save/analyses_16S/202111_Rotenone/
```{bash}
......@@ -151,9 +151,9 @@ qsub -cwd -V -N multiqc -o LOGS -e LOGS -b y "conda activate multiqc-1.8 && mult
```
Numéro du job **fastqc** sur le cluster de migale: 4045739.1-40:1
Numéro du job **fastqc** sur le cluster de calcul de la plateforme Migale: 4045739.1-40:1
Numéro du job **multiqc** sur le cluster de migale: 4045740
Numéro du job **multiqc** sur le cluster de calcul de la plateforme Migale: 4045740
Lien vers le [rapport multiqc](MULTIQC/multiqc_report.html)
......@@ -243,7 +243,7 @@ qacct -j 3982109
```
Numéro du job **preprocess** sur le cluster de migale: 4046130
Numéro du job **preprocess** sur le cluster de calcul de la plateforme Migale: 4046130
Les paramètres suivants ont été choisis :
......@@ -278,7 +278,7 @@ qacct -j 4046530
```
Numéro du job **clustering** sur le cluster de migale: 4046530
Numéro du job **clustering** sur le cluster de calcul de la plateforme Migale: 4046530
### Remove Chimera
......@@ -291,7 +291,7 @@ qacct -j 4046537
```
Numéro du job **chimera** sur le cluster de migale: 4046537
Numéro du job **chimera** sur le cluster de calcul de la plateforme Migale: 4046537
Lien vers le [rapport remove_chimera](FROGS/remove_chimera.html)
......@@ -318,7 +318,7 @@ qsub -cwd -V -N filters -o LOGS -e LOGS -pe thread 8 -R y -b y "conda activate f
qacct -j 4046541
```
Numéro du job **filters** sur le cluster de migale: 4046541
Numéro du job **filters** sur le cluster de calcul de la plateforme Migale: 4046541
Lien vers le [rapport filters](FROGS/filters.html)
......@@ -346,11 +346,11 @@ qsub -cwd -V -N affiliations_stats -o LOGS -e LOGS -b y "conda activate frogs-3.
```
Numéro du job **affiliation** sur le cluster de migale: 4046545
Numéro du job **affiliation** sur le cluster de calcul de la plateforme Migale: 4046545
Lien vers le [rapport affiliation_OTU](FROGS/affiliation.html)
Numéro du job **affiliation_stats** sur le cluster de migale: 4046552
Numéro du job **affiliation_stats** sur le cluster de calcul de la plateforme Migale: 4046552
Lien vers le [rapport affiliations_stats](FROGS/affiliations_stats.html)
......@@ -365,7 +365,7 @@ qsub -cwd -V -N biom_to_tsv -o LOGS -e LOGS -b y "conda activate frogs-3.2.2 &&
```
Numéro du job **biom_to_tsv** sur le cluster de migale: 4046554
Numéro du job **biom_to_tsv** sur le cluster de calcul de la plateforme Migale: 4046554
Je vais "rectifier" toutes les multis affiliations sur **affiliationExplorer** en important **multi_aff.tsv** et **affiliation.biom**
......@@ -381,7 +381,7 @@ qsub -cwd -V -N affiliations_stats_cleaned -o LOGS -e LOGS -b y "conda activate
```
Numéro du job **affiliations_stats_cleaned** sur le cluster de migale: 4049992
Numéro du job **affiliations_stats_cleaned** sur le cluster de calcul de la plateforme Migale: 4049992
Lien vers le [rapport affiliations_stats_cleaned](FROGS/affiliations_stats_cleaned.html)
......@@ -401,7 +401,7 @@ qsub -cwd -V -N tree -o LOGS -e LOGS -b y "conda activate frogs-3.2.2 && tree.py
```
Numéro du job **tree** sur le cluster de migale: 4049993
Numéro du job **tree** sur le cluster de calcul de la plateforme Migale: 4049993
Lien vers l'arbre [Tree](FROGS/tree.html)
......
......@@ -13,7 +13,8 @@
<title>Analyses 16s projet Rotenone Paula Perez Pardo</title>
<script src="site_libs/jquery-3.5.1/jquery.min.js"></script>
<script src="site_libs/header-attrs-2.11/header-attrs.js"></script>
<script src="site_libs/jquery-3.6.0/jquery-3.6.0.min.js"></script>
<meta name="viewport" content="width=device-width, initial-scale=1" />
<link href="site_libs/bootstrap-3.3.5/css/bootstrap.min.css" rel="stylesheet" />
<script src="site_libs/bootstrap-3.3.5/js/bootstrap.min.js"></script>
......@@ -37,7 +38,7 @@
<script src="site_libs/highlightjs-9.12.0/highlight.js"></script>
<link href="site_libs/pagedtable-1.1/css/pagedtable.css" rel="stylesheet" />
<script src="site_libs/pagedtable-1.1/js/pagedtable.js"></script>
<script src="site_libs/htmlwidgets-1.5.3/htmlwidgets.js"></script>
<script src="site_libs/htmlwidgets-1.5.4/htmlwidgets.js"></script>
<link href="site_libs/datatables-css-0.0.0/datatables-crosstalk.css" rel="stylesheet" />
<script src="site_libs/datatables-binding-0.18/datatables.js"></script>
<link href="site_libs/dt-core-1.10.20/css/jquery.dataTables.min.css" rel="stylesheet" />
......@@ -272,7 +273,7 @@ div.tocify {
<h1 class="title toc-ignore">Analyses 16s projet Rotenone Paula Perez Pardo</h1>
<h4 class="author">Magali Monnoye</h4>
<address class="author_afil">
INRAE - MICALIS<br><h4 class="date">2021-11-16 (Last updated: 2021-11-17)</h4>
INRAE - MICALIS<br><h4 class="date">2021-11-16 (Last updated: 2021-11-18)</h4>
</div>
......@@ -532,7 +533,7 @@ Je supprime l’échantillon 2.1 car il possède trop peu de reads
<p>Le groupe <strong>Rotenone</strong> avec rotenone</p>
</div>
<div id="visualisation-de-labondance-par-échantillon" class="section level2 tabset">
<h2>Visualisation de l’abondance par échantillon</h2>
<h2 class="tabset">Visualisation de l’abondance par échantillon</h2>
<div id="abondances-brutes" class="section level3">
<h3>Abondances brutes</h3>
<p><img src="report_Rotenone_files/figure-html/01-plot%20abondances-1.png" width="1008" /></p>
......@@ -545,7 +546,7 @@ Je supprime l’échantillon 2.1 car il possède trop peu de reads
<div id="composition-des-communautés" class="section level2">
<h2>Composition des communautés</h2>
<div id="représentation-des-communautés-au-niveau-phylum" class="section level3 tabset">
<h3>Représentation des communautés au niveau Phylum</h3>
<h3 class="tabset">Représentation des communautés au niveau Phylum</h3>
<ul>
<li>Nombre d’OTUs par Phylum:</li>
</ul>
......@@ -562,13 +563,13 @@ Je supprime l’échantillon 2.1 car il possède trop peu de reads
<div class="alert alert-info" role="alert">
Abandance Relative = nb total des individus d’une éspèce par rapport au nb total des individus de toutes les espèces présentes
</div>
<div id="htmlwidget-3c21df44dc7fe2b4a359" style="width:100%;height:auto;" class="datatables html-widget"></div>
<script type="application/json" data-for="htmlwidget-3c21df44dc7fe2b4a359">{"x":{"filter":"none","extensions":["Buttons"],"data":[["Bacteroidota","Firmicutes","Deferribacterota","Proteobacteria","Desulfobacterota","Actinobacteriota"],[46.1401239798421,52.5130446416626,0.102573250680105,0.0535164786157071,1.19074164919948,0],[18.4365410734946,80.4316112480507,0.684139041199256,0.0603652095175814,0.311886915840837,0.0754565118969767],[28.6539895600298,67.9903057419836,2.28933631618195,0.108128262490679,0.950782997762864,0.00745712155108128],[32.1091242549289,67.3360843649702,0.206327372764787,0.0871160018340211,0.160476845483723,0.10087116001834],[22.6219394640447,74.6365914786967,2.29805282436861,0.0385579332947754,0.404858299595142,0],[14.4727919986438,82.124088828615,2.59789794880488,0.0339040515341583,0.771317172402102,0],[24.0566348370102,72.4399078037537,1.98551201843925,0.0296345077378992,1.48172538689496,0.00658544616397761],[23.7345849438616,74.3005705871526,1.01693355420578,0.312902632063317,0.635008282716731,0],[21.5667697217513,75.1770220404907,2.54812007579535,0.1695422359629,0.538545925999801,0],[26.5318162663295,72.338811630847,0.876527602191319,0.0421407501053519,0.210703750526759,0],[40.3927855711423,57.7154308617234,0.733466933867735,0.152304609218437,1.0060120240481,0],[13.0909606656581,81.9875189107413,3.7017776096823,0.113464447806354,1.10627836611195,0],[18.4444909052896,78.988082793226,1.73949404139661,0.0250888563662973,0.802843403721514,0],[4.06497257922719,93.7329928412944,1.85456524469377,0.0209318876376272,0.326537447146984,0],[10.9652070516466,86.9151631081011,1.84562890968309,0.0930569198159541,0.180944010753244,0],[24.0481783943021,75.4782414140284,0.0633926240817392,0.171532982809412,0.182719916470895,0.0559346683074169],[19.1250204817303,80.3178764542028,0.242503686711453,0.131083073898083,0.180239226609864,0.00327707684745207],[9.88627179309549,89.0370626948389,0.239579725204942,0.637917099642074,0.187622676365316,0.0115460108532502],[18.2108323326803,81.4858117929596,0.0789989256146116,0.0505593123933515,0.154837894204639,0.0189597421475068]],"container":"<table class=\"display\">\n <thead>\n <tr>\n <th> <\/th>\n <th>1_1<\/th>\n <th>1_2<\/th>\n <th>1_3<\/th>\n <th>2_2<\/th>\n <th>2_3<\/th>\n <th>2_4<\/th>\n <th>2_5<\/th>\n <th>2_6<\/th>\n <th>2_7<\/th>\n <th>3_1<\/th>\n <th>3_2<\/th>\n <th>3_3<\/th>\n <th>3_4<\/th>\n <th>3_5<\/th>\n <th>3_6<\/th>\n <th>4_1<\/th>\n <th>4_2<\/th>\n <th>4_3<\/th>\n <th>4_4<\/th>\n <\/tr>\n <\/thead>\n<\/table>","options":{"pageLength":20,"scrollX":true,"language":{"search":"Filter:"},"dom":"Bfrtip","buttons":["copy","csv","excel"],"columnDefs":[{"className":"dt-right","targets":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19]},{"orderable":false,"targets":0}],"order":[],"autoWidth":false,"orderClasses":false,"lengthMenu":[10,20,25,50,100]}},"evals":[],"jsHooks":[]}</script>
<div id="htmlwidget-36bbc39edf955131f7fe" style="width:100%;height:auto;" class="datatables html-widget"></div>
<script type="application/json" data-for="htmlwidget-36bbc39edf955131f7fe">{"x":{"filter":"none","extensions":["Buttons"],"data":[["Bacteroidota","Firmicutes","Deferribacterota","Proteobacteria","Desulfobacterota","Actinobacteriota"],[46.1401239798421,52.5130446416626,0.102573250680105,0.0535164786157071,1.19074164919948,0],[18.4365410734946,80.4316112480507,0.684139041199256,0.0603652095175814,0.311886915840837,0.0754565118969767],[28.6539895600298,67.9903057419836,2.28933631618195,0.108128262490679,0.950782997762864,0.00745712155108128],[32.1091242549289,67.3360843649702,0.206327372764787,0.0871160018340211,0.160476845483723,0.10087116001834],[22.6219394640447,74.6365914786967,2.29805282436861,0.0385579332947754,0.404858299595142,0],[14.4727919986438,82.124088828615,2.59789794880488,0.0339040515341583,0.771317172402102,0],[24.0566348370102,72.4399078037537,1.98551201843925,0.0296345077378992,1.48172538689496,0.00658544616397761],[23.7345849438616,74.3005705871526,1.01693355420578,0.312902632063317,0.635008282716731,0],[21.5667697217513,75.1770220404907,2.54812007579535,0.1695422359629,0.538545925999801,0],[26.5318162663295,72.338811630847,0.876527602191319,0.0421407501053519,0.210703750526759,0],[40.3927855711423,57.7154308617234,0.733466933867735,0.152304609218437,1.0060120240481,0],[13.0909606656581,81.9875189107413,3.7017776096823,0.113464447806354,1.10627836611195,0],[18.4444909052896,78.988082793226,1.73949404139661,0.0250888563662973,0.802843403721514,0],[4.06497257922719,93.7329928412944,1.85456524469377,0.0209318876376272,0.326537447146984,0],[10.9652070516466,86.9151631081011,1.84562890968309,0.0930569198159541,0.180944010753244,0],[24.0481783943021,75.4782414140284,0.0633926240817392,0.171532982809412,0.182719916470895,0.0559346683074169],[19.1250204817303,80.3178764542028,0.242503686711453,0.131083073898083,0.180239226609864,0.00327707684745207],[9.88627179309549,89.0370626948389,0.239579725204942,0.637917099642074,0.187622676365316,0.0115460108532502],[18.2108323326803,81.4858117929596,0.0789989256146116,0.0505593123933515,0.154837894204639,0.0189597421475068]],"container":"<table class=\"display\">\n <thead>\n <tr>\n <th> <\/th>\n <th>1_1<\/th>\n <th>1_2<\/th>\n <th>1_3<\/th>\n <th>2_2<\/th>\n <th>2_3<\/th>\n <th>2_4<\/th>\n <th>2_5<\/th>\n <th>2_6<\/th>\n <th>2_7<\/th>\n <th>3_1<\/th>\n <th>3_2<\/th>\n <th>3_3<\/th>\n <th>3_4<\/th>\n <th>3_5<\/th>\n <th>3_6<\/th>\n <th>4_1<\/th>\n <th>4_2<\/th>\n <th>4_3<\/th>\n <th>4_4<\/th>\n <\/tr>\n <\/thead>\n<\/table>","options":{"pageLength":20,"scrollX":true,"language":{"search":"Filter:"},"dom":"Bfrtip","buttons":["copy","csv","excel"],"columnDefs":[{"className":"dt-right","targets":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19]},{"orderable":false,"targets":0}],"order":[],"autoWidth":false,"orderClasses":false,"lengthMenu":[10,20,25,50,100]}},"evals":[],"jsHooks":[]}</script>
<ul>
<li>Relatives abondances par groupes:</li>
</ul>
<div id="htmlwidget-2fe72b36eb90f5d0414d" style="width:100%;height:auto;" class="datatables html-widget"></div>
<script type="application/json" data-for="htmlwidget-2fe72b36eb90f5d0414d">{"x":{"filter":"none","extensions":["Buttons"],"data":[["Rotenone","Vehicule"],[18.4760536041101,25.7547222037341],[79.7996992501963,71.8832474150418],[1.13759353031276,1.52543248916],[0.143807993969294,0.099296368116782],[0.433873871595926,0.716149275099516],[0.0089717498155626,0.0211522488478195]],"container":"<table class=\"display\">\n <thead>\n <tr>\n <th> <\/th>\n <th>Bacteroidota<\/th>\n <th>Firmicutes<\/th>\n <th>Deferribacterota<\/th>\n <th>Proteobacteria<\/th>\n <th>Desulfobacterota<\/th>\n <th>Actinobacteriota<\/th>\n <\/tr>\n <\/thead>\n<\/table>","options":{"pageLength":10,"scrollX":true,"language":{"search":"Filter:"},"dom":"Bfrtip","buttons":["copy","csv","excel"],"columnDefs":[{"className":"dt-right","targets":[1,2,3,4,5,6]},{"orderable":false,"targets":0}],"order":[],"autoWidth":false,"orderClasses":false}},"evals":[],"jsHooks":[]}</script>
<div id="htmlwidget-ca13187ce50471b9355f" style="width:100%;height:auto;" class="datatables html-widget"></div>
<script type="application/json" data-for="htmlwidget-ca13187ce50471b9355f">{"x":{"filter":"none","extensions":["Buttons"],"data":[["Rotenone","Vehicule"],[18.4760536041101,25.7547222037341],[79.7996992501963,71.8832474150418],[1.13759353031276,1.52543248916],[0.143807993969294,0.099296368116782],[0.433873871595926,0.716149275099516],[0.0089717498155626,0.0211522488478195]],"container":"<table class=\"display\">\n <thead>\n <tr>\n <th> <\/th>\n <th>Bacteroidota<\/th>\n <th>Firmicutes<\/th>\n <th>Deferribacterota<\/th>\n <th>Proteobacteria<\/th>\n <th>Desulfobacterota<\/th>\n <th>Actinobacteriota<\/th>\n <\/tr>\n <\/thead>\n<\/table>","options":{"pageLength":10,"scrollX":true,"language":{"search":"Filter:"},"dom":"Bfrtip","buttons":["copy","csv","excel"],"columnDefs":[{"className":"dt-right","targets":[1,2,3,4,5,6]},{"orderable":false,"targets":0}],"order":[],"autoWidth":false,"orderClasses":false}},"evals":[],"jsHooks":[]}</script>
</div>
<div id="plot-composition-phylum" class="section level4">
<h4>Plot composition Phylum</h4>
......@@ -598,12 +599,12 @@ Le test wilcox compare Vehicule à Rotenone
</div>
</div>
<div id="représentation-des-communautés-au-niveau-family" class="section level3 tabset">
<h3>Représentation des communautés au niveau Family</h3>
<h3 class="tabset">Représentation des communautés au niveau Family</h3>
<ul>
<li>Nombre d’OTUs par Family:</li>
</ul>
<pre><code>##
## \tuncultured bacterium [Eubacterium] coprostanoligenes group
## \tuncultured bacterium [Eubacterium] coprostanoligenes group
## 2 2
## Acholeplasmataceae Anaerovoracaceae
## 1 5
......@@ -640,13 +641,13 @@ Le test wilcox compare Vehicule à Rotenone
<ul>
<li>Relative Abondance par échantillon:</li>
</ul>
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<ul>
<li>Relative Abondance par groupe:</li>
</ul>
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<script type="application/json" data-for="htmlwidget-d86ead1bd10538021a9c">{"x":{"filter":"none","extensions":["Buttons"],"data":[["Vehicule","Rotenone"],[3.49758026335939,2.41488781384502],[1.82518921481032,1.43070141489576],[9.54127488374006,6.94859696515142],[0.569392288008008,0.396036367457097],[0.571882361612331,0.111751370382395],[9.74940319220402,7.17407967237846],[48.82267293371,57.7886430790042],[1.54918463406373,1.44035336633839],[0.0719844251835365,0.0940949980308504],[1.31930203257697,0.356285342109803],[0.475166889791749,0.380924384717717],[0.0845646847258823,0.0449726407786422],[2.83102993367589,1.24038741834733],[0.0247314835932361,0.0122668286494586],[0.66232093202624,0.405003063119775],[0.0312948575852526,0.0265116238413762],[3.82577712717169,6.26284152368674],[0.0911762228267602,0.0223027339597055],[1.73174249984755,3.40681895931888],[0.506899324837168,0.427884460785942],[1.14167597907586,0.000418637752752543],[0.0323807053172846,0.0374439738219156],[0.0842165333508565,0.0765636041561409],[0.100678373362437,0.0835410537840684],[7.8347371254783,5.54931340888109],[0.694091422158689,2.18057212293349],[1.52543248916,1.13759353031276],[0.0600615564859473,0.101055928264202],[0.00685410631355019,0.00530809188317667],[0.716149275099516,0.433873871595926],[0.0211522488478195,0.0089717498155626]],"container":"<table class=\"display\">\n <thead>\n <tr>\n <th> <\/th>\n <th>Muribaculaceae<\/th>\n <th>Marinifilaceae<\/th>\n <th>Rikenellaceae<\/th>\n <th>Tannerellaceae<\/th>\n <th>Prevotellaceae<\/th>\n <th>Bacteroidaceae<\/th>\n <th>Lachnospiraceae<\/th>\n <th>Ruminococcaceae<\/th>\n <th>Anaerovoracaceae<\/th>\n <th>Peptostreptococcaceae<\/th>\n <th>Clostridiaceae<\/th>\n <th>Peptococcaceae<\/th>\n <th>Erysipelotrichaceae<\/th>\n <th>Staphylococcaceae<\/th>\n <th>Enterococcaceae<\/th>\n <th>Streptococcaceae<\/th>\n <th>Lactobacillaceae<\/th>\n <th>Acholeplasmataceae<\/th>\n <th>Unknown<\/th>\n <th>uncultured bacterium<\/th>\n <th> \tuncultured bacterium<\/th>\n <th>Rhodospirillaceae<\/th>\n <th>Butyricicoccaceae<\/th>\n <th>UCG-010<\/th>\n <th>Oscillospiraceae<\/th>\n <th>[Eubacterium] coprostanoligenes group<\/th>\n <th>Deferribacteraceae<\/th>\n <th>Enterobacteriaceae<\/th>\n <th>Morganellaceae<\/th>\n <th>Desulfovibrionaceae<\/th>\n <th>Bifidobacteriaceae<\/th>\n <\/tr>\n <\/thead>\n<\/table>","options":{"pageLength":10,"scrollX":true,"language":{"search":"Filter:"},"dom":"Bfrtip","buttons":["copy","csv","excel"],"columnDefs":[{"className":"dt-right","targets":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31]},{"orderable":false,"targets":0}],"order":[],"autoWidth":false,"orderClasses":false}},"evals":[],"jsHooks":[]}</script>
</div>
<div id="plot-composition-family" class="section level4">
<h4>Plot composition Family</h4>
......@@ -676,7 +677,7 @@ Le test wilcox compare Vehicule à Rotenone
</div>
</div>
<div id="zoom-au-niveau-family-dans-chacun-des-phylums" class="section level3 tabset">
<h3>Zoom au niveau Family dans chacun des Phylums</h3>
<h3 class="tabset">Zoom au niveau Family dans chacun des Phylums</h3>
<p>Les 6 phylums d’intérêts sont les Actinobacteriota, les Bacteroidota, les Desulfobacterota, les Fibrobacterota, les Firmicutes et les Proteobacteria.</p>
<div id="actinobacteriota" class="section level4">
<h4>Actinobacteriota</h4>
......@@ -740,19 +741,19 @@ sample_sums(frogs.data.rare)[1:5]</code></pre>
<li><p>Shannon maximal -&gt; Tous les individus sont équitablement répartis entre les espèces.</p></li>
</ul></li>
<li><p><strong>InvSIMPSON</strong> sensible aux variations d’importance des espèces les plus abondantes (Indice de dominance).</p>
L’inverse de Simpson permet de faire varier l’indice dans le même sens que la diversité :plus la diversité spécifique est élevée plus l’indice est fort.</li>
<p>L’inverse de Simpson permet de faire varier l’indice dans le même sens que la diversité :plus la diversité spécifique est élevée plus l’indice est fort.</p></li>
</ul>
</div>
<p><img src="report_Rotenone_files/figure-html/22-plot-richness-1.png" width="960" /></p>
</div>
<div id="richness-table" class="section level3">
<h3>Richness Table</h3>
<div id="htmlwidget-2a6e9f32e46974fa0ed5" style="width:100%;height:auto;" class="datatables html-widget"></div>
<script type="application/json" data-for="htmlwidget-2a6e9f32e46974fa0ed5">{"x":{"filter":"none","extensions":["Buttons"],"data":[["X1_1","X1_2","X1_3","X2_2","X2_3","X2_4","X2_5","X2_6","X2_7","X3_1","X3_2","X3_3","X3_4","X3_5","X3_6","X4_1","X4_2","X4_3","X4_4"],[438,455,441,387,394,450,453,419,408,410,400,438,474,454,389,394,426,433,453],[498.022222222222,484.555555555556,485.264150943396,416.8125,425.109090909091,481.685185185185,502.109090909091,444.018867924528,449.108695652174,448.294117647059,434.071428571429,463.333333333333,514.32,477.459016393443,428.06,449.222222222222,477.483870967742,466.549019607843,498.122448979592],[18.3223529902082,10.384124973158,13.9925073869651,10.7249113460639,10.7298762293134,10.9166372781731,14.9769926526491,9.25756236760888,13.706354356793,12.6923168959614,12.1929466347107,9.01120795760091,13.2440665730557,8.59470994681055,12.9381701259813,17.1970734903368,17.9876972901768,11.5243764088314,14.4645805277339],[3.9828472780223,4.1374581138565,4.04505260402129,3.83081383646944,3.13118264635815,3.7998228894175,4.04254846322319,3.64309188396129,3.48851608159785,3.14351690764125,3.86617229893245,3.88590399121928,4.11409876413577,3.52657110945986,3.349739322311,2.75138495173776,3.34092525336477,3.53073641740392,3.71417114373337],[21.4536917251132,17.6411509196866,21.3262233311918,17.6406851352942,6.63503251487805,10.4152069283862,19.8707104691554,9.30582301826565,9.55347011084472,5.90681159250937,16.0261831510681,14.5896973328278,16.0261843168932,6.40177676475277,6.04901569456807,4.02797984209601,8.20095804013175,10.528544863613,14.0670565315506],["1_1","1_2","1_3","2_2","2_3","2_4","2_5","2_6","2_7","3_1","3_2","3_3","3_4","3_5","3_6","4_1","4_2","4_3","4_4"],["Vehicule","Vehicule","Vehicule","Vehicule","Vehicule","Vehicule","Vehicule","Vehicule","Vehicule","Rotenone","Rotenone","Rotenone","Rotenone","Rotenone","Rotenone","Rotenone","Rotenone","Rotenone","Rotenone"],[1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1],[5,6,6,6,5,5,6,5,5,5,5,5,5,5,5,6,6,6,6],[7,8,8,8,7,7,8,7,7,7,7,7,7,7,7,8,8,8,8],[16,17,18,18,16,17,18,17,17,17,17,16,16,16,16,18,17,18,18],[27,28,30,30,28,30,30,30,30,29,29,29,29,27,27,30,29,31,30],[59,63,62,58,55,60,60,63,61,57,62,60,61,58,57,63,65,63,65],[73,75,75,69,66,71,72,73,73,67,73,69,72,69,69,74,76,75,78],["22,423","19,879","26,820","21,810","25,935","23,596","30,370","21,732","20,054","23,730","24,950","21,152","23,915","23,887","19,343","26,817","30,515","34,644","31,646"],[22423,19879,26820,21810,25935,23596,30370,21732,20054,23730,24950,21152,23915,23887,19343,26817,30515,34644,31646]],"container":"<table class=\"display\">\n <thead>\n <tr>\n <th> <\/th>\n <th>Observed<\/th>\n <th>Chao1<\/th>\n <th>se.chao1<\/th>\n <th>Shannon<\/th>\n <th>InvSimpson<\/th>\n <th>Name<\/th>\n <th>Group<\/th>\n <th>Nb_domain<\/th>\n <th>Nb_phylum<\/th>\n <th>Nb_class<\/th>\n <th>Nb_order<\/th>\n <th>Nb_family<\/th>\n <th>Nb_genus<\/th>\n <th>Nb_species<\/th>\n <th>Nb_sequences<\/th>\n <th>Depth<\/th>\n <\/tr>\n <\/thead>\n<\/table>","options":{"pageLength":10,"scrollX":true,"language":{"search":"Filter:"},"dom":"Bfrtip","buttons":["copy","csv","excel"],"columnDefs":[{"className":"dt-right","targets":[1,2,3,4,5,8,9,10,11,12,13,14,16]},{"orderable":false,"targets":0}],"order":[],"autoWidth":false,"orderClasses":false}},"evals":[],"jsHooks":[]}</script>
<div id="htmlwidget-c787e30b832d190af950" style="width:100%;height:auto;" class="datatables html-widget"></div>
<script type="application/json" data-for="htmlwidget-c787e30b832d190af950">{"x":{"filter":"none","extensions":["Buttons"],"data":[["X1_1","X1_2","X1_3","X2_2","X2_3","X2_4","X2_5","X2_6","X2_7","X3_1","X3_2","X3_3","X3_4","X3_5","X3_6","X4_1","X4_2","X4_3","X4_4"],[438,455,441,387,394,450,453,419,408,410,400,438,474,454,389,394,426,433,453],[498.022222222222,484.555555555556,485.264150943396,416.8125,425.109090909091,481.685185185185,502.109090909091,444.018867924528,449.108695652174,448.294117647059,434.071428571429,463.333333333333,514.32,477.459016393443,428.06,449.222222222222,477.483870967742,466.549019607843,498.122448979592],[18.3223529902082,10.384124973158,13.9925073869651,10.7249113460639,10.7298762293134,10.9166372781731,14.9769926526491,9.25756236760888,13.706354356793,12.6923168959614,12.1929466347107,9.01120795760091,13.2440665730557,8.59470994681055,12.9381701259813,17.1970734903368,17.9876972901768,11.5243764088314,14.4645805277339],[3.9828472780223,4.1374581138565,4.04505260402129,3.83081383646944,3.13118264635815,3.7998228894175,4.04254846322319,3.64309188396129,3.48851608159785,3.14351690764125,3.86617229893245,3.88590399121928,4.11409876413577,3.52657110945986,3.349739322311,2.75138495173776,3.34092525336477,3.53073641740392,3.71417114373337],[21.4536917251132,17.6411509196866,21.3262233311918,17.6406851352942,6.63503251487805,10.4152069283862,19.8707104691554,9.30582301826565,9.55347011084472,5.90681159250937,16.0261831510681,14.5896973328278,16.0261843168932,6.40177676475277,6.04901569456807,4.02797984209601,8.20095804013175,10.528544863613,14.0670565315506],["1_1","1_2","1_3","2_2","2_3","2_4","2_5","2_6","2_7","3_1","3_2","3_3","3_4","3_5","3_6","4_1","4_2","4_3","4_4"],["Vehicule","Vehicule","Vehicule","Vehicule","Vehicule","Vehicule","Vehicule","Vehicule","Vehicule","Rotenone","Rotenone","Rotenone","Rotenone","Rotenone","Rotenone","Rotenone","Rotenone","Rotenone","Rotenone"],[1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1],[5,6,6,6,5,5,6,5,5,5,5,5,5,5,5,6,6,6,6],[7,8,8,8,7,7,8,7,7,7,7,7,7,7,7,8,8,8,8],[16,17,18,18,16,17,18,17,17,17,17,16,16,16,16,18,17,18,18],[27,28,30,30,28,30,30,30,30,29,29,29,29,27,27,30,29,31,30],[59,63,62,58,55,60,60,63,61,57,62,60,61,58,57,63,65,63,65],[73,75,75,69,66,71,72,73,73,67,73,69,72,69,69,74,76,75,78],["22,423","19,879","26,820","21,810","25,935","23,596","30,370","21,732","20,054","23,730","24,950","21,152","23,915","23,887","19,343","26,817","30,515","34,644","31,646"],[22423,19879,26820,21810,25935,23596,30370,21732,20054,23730,24950,21152,23915,23887,19343,26817,30515,34644,31646]],"container":"<table class=\"display\">\n <thead>\n <tr>\n <th> <\/th>\n <th>Observed<\/th>\n <th>Chao1<\/th>\n <th>se.chao1<\/th>\n <th>Shannon<\/th>\n <th>InvSimpson<\/th>\n <th>Name<\/th>\n <th>Group<\/th>\n <th>Nb_domain<\/th>\n <th>Nb_phylum<\/th>\n <th>Nb_class<\/th>\n <th>Nb_order<\/th>\n <th>Nb_family<\/th>\n <th>Nb_genus<\/th>\n <th>Nb_species<\/th>\n <th>Nb_sequences<\/th>\n <th>Depth<\/th>\n <\/tr>\n <\/thead>\n<\/table>","options":{"pageLength":10,"scrollX":true,"language":{"search":"Filter:"},"dom":"Bfrtip","buttons":["copy","csv","excel"],"columnDefs":[{"className":"dt-right","targets":[1,2,3,4,5,8,9,10,11,12,13,14,16]},{"orderable":false,"targets":0}],"order":[],"autoWidth":false,"orderClasses":false}},"evals":[],"jsHooks":[]}</script>
</div>
</div>
<div id="statistiques-sur-la-diversité" class="section level2 tabset">
<h2>Statistiques sur la diversité</h2>
<h2 class="tabset">Statistiques sur la diversité</h2>
<div id="statistiques-sur-richness-observed" class="section level3">
<h3>Statistiques sur Richness Observed</h3>
<div id="anova-sur-la-richness-observed" class="section level4">
......@@ -903,7 +904,7 @@ L’inverse de Simpson permet de faire varier l’indice dans le même sens que
<p><img src="report_Rotenone_files/figure-html/23-dist-as-heatmap-1.png" width="1152" /></p>
</div>
<div id="ordination-des-échantillons" class="section level3 tabset">
<h3>Ordination des échantillons</h3>
<h3 class="tabset">Ordination des échantillons</h3>
<div class="alert alert-info" role="alert">
<p>On va faire une MDS (non-parametric multi-dimensional scaling) aussi appelé PCoA pour avoir une représentation en 2D de la distance entre tous les échantillons. Permet de visusaliser les similitudes entre les groupes.</p>
La mise à l’échelle multidimensionnelle (MDS) est une approche populaire pour représenter graphiquement les relations entre des objets (par exemple, des tracés ou des échantillons) dans un espace multidimensionnel.
......@@ -1000,13 +1001,13 @@ Analyse multivariée de la variance par permutations basée sur les matrices de
</div>
</div>
<div id="clustering-des-échantillons" class="section level3 tabset">
<h3>Clustering des échantillons</h3>
<h3 class="tabset">Clustering des échantillons</h3>
<p>Clustering des échantillons pour vérifier s’ils se regroupent par groupe (ou autre).</p>
<div class="alert alert-info" role="alert">
<ul>
<li><p><strong>Ward</strong> : c’est la plus courante. Elle consiste à réunir les deux clusters dont le regroupement fera le moins baisser l’inertie interclasse. C’est la distance de Ward qui est utilisée : la distance entre deux classes est celle de leurs barycentres au carré, pondérée par les effectifs des deux clusters. Cette technique tend à regrouper les petites classes entre elles.</p></li>
<li><p><strong>Median</strong> : moyenne de tous les liens, qu’ils soient entre observations de deux clusters différents ou intraclasses. Cette méthode est la seule qui s’attache directement au cluster obtenu et non aux caractéristiques des clusters candidats.</p></li>
<li><strong>Average</strong> : le logiciel mesure tous les liens entre chaque observation du cluster A et chaque observation du cluster B et en fait une moyenne. C’est une des méthodes les plus efficaces. Elle tend à réunir des clusters aux inerties faibles.</li>
<li><p><strong>Average</strong> : le logiciel mesure tous les liens entre chaque observation du cluster A et chaque observation du cluster B et en fait une moyenne. C’est une des méthodes les plus efficaces. Elle tend à réunir des clusters aux inerties faibles.</p></li>
</ul>
</div>
<div id="clustering-sur-la-matrice-de-bray-curtis" class="section level4">
......@@ -1027,7 +1028,7 @@ Analyse multivariée de la variance par permutations basée sur les matrices de
</div>
</div>
<div id="network" class="section level3 tabset">
<h3>Network</h3>
<h3 class="tabset">Network</h3>
<div id="network-bray-curtis" class="section level4">
<h4>Network Bray curtis</h4>
<div class="alert alert-success" role="alert">
......@@ -1052,7 +1053,7 @@ Default 0.4. The maximum ecological distance (as defined by distance) allowed be
</div>
</div>
<div id="abondances-différentielles-entre-les-2-groupes" class="section level2 tabset">
<h2>Abondances différentielles entre les 2 groupes</h2>
<h2 class="tabset">Abondances différentielles entre les 2 groupes</h2>
<div class="alert comment">
Pour les analyses suivantes, je prends p-valeur ajustée <strong>pval=0.05</strong>, <strong>min.abundance=30</strong> et <strong>lfc.threshold = 2</strong>
</div>
......@@ -1067,8 +1068,8 @@ table(get_variable(data, &quot;Group&quot;))</code></pre>
<div id="table-des-otus-différentiels" class="section level3">
<h3>Table des OTUs différentiels</h3>
<p>Avec <strong>pval=0.05</strong></p>
<div id="htmlwidget-a82d7a0a6e58381a86c1" style="width:100%;height:auto;" class="datatables html-widget"></div>
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</div>
<div id="heatmap" class="section level3">
<h3>Heatmap</h3>
......@@ -1099,38 +1100,33 @@ table(get_variable(data, &quot;Group&quot;))</code></pre>
<p>Représentations avec <strong>pval = 0.05</strong> / <strong>min abundance = 30</strong> / <strong>log2foldchange = 2</strong></p>
<p>Graphique sur lequel n’est affiché que la classification d’un OTU que si elle est plus précise que la famille (qui apparait déjà via la couleur)</p>
<p><img src="report_Rotenone_files/figure-html/46-divergence-1.png" width="960" /></p>
<pre><code>## R version 4.0.3 (2020-10-10)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: CentOS Linux 7 (Core)
<pre><code>## R version 4.1.1 (2021-08-10)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 19042)
##
## Matrix products: default
## BLAS: /usr/local/public/R-4.0.3/lib64/R/lib/libRblas.so
## LAPACK: /usr/local/public/R-4.0.3/lib64/R/lib/libRlapack.so
##
## locale:
## [1] LC_CTYPE=fr_FR.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=fr_FR.UTF-8 LC_COLLATE=fr_FR.UTF-8
## [5] LC_MONETARY=fr_FR.UTF-8 LC_MESSAGES=fr_FR.UTF-8
## [7] LC_PAPER=fr_FR.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=fr_FR.UTF-8 LC_IDENTIFICATION=C
## [1] LC_COLLATE=French_France.1252 LC_CTYPE=French_France.1252
## [3] LC_MONETARY=French_France.1252 LC_NUMERIC=C
## [5] LC_TIME=French_France.1252
##
## attached base packages:
## [1] parallel stats graphics grDevices utils datasets methods
## [8] base
##
## other attached packages:
## [1] biomformat_1.18.0 scales_1.1.1
## [1] biomformat_1.20.0 scales_1.1.1
## [3] gridExtra_2.3 reshape2_1.4.4
## [5] openxlsx_4.2.4 ggpubr_0.4.0
## [7] ape_5.5 vegan_2.5-7
## [9] lattice_0.20-44 permute_0.9-5
## [11] cowplot_1.1.1 plotly_4.9.4.1
## [13] data.table_1.14.0 phyloseq.extended_0.1.1.4
## [15] phyloseq_1.34.0 forcats_0.5.1
## [13] data.table_1.14.0 phyloseq.extended_0.1.1.6
## [15] phyloseq_1.36.0 forcats_0.5.1
## [17] stringr_1.4.0 dplyr_1.0.7
## [19] purrr_0.3.4 readr_2.0.0
## [21] tidyr_1.1.3 tibble_3.1.2
## [19] purrr_0.3.4 readr_2.0.1
## [21] tidyr_1.1.3 tibble_3.1.4
## [23] ggplot2_3.3.5 tidyverse_1.3.1
## [25] DT_0.18 kableExtra_1.3.4
##
......@@ -1138,65 +1134,66 @@ table(get_variable(data, &quot;Group&quot;))</code></pre>
## [1] readxl_1.3.1 backports_1.2.1
## [3] systemfonts_1.0.2 plyr_1.8.6
## [5] igraph_1.2.6 lazyeval_0.2.2
## [7] splines_4.0.3 BiocParallel_1.24.1
## [9] crosstalk_1.1.1 GenomeInfoDb_1.26.7
## [7] splines_4.1.1 BiocParallel_1.26.2
## [9] crosstalk_1.1.1 GenomeInfoDb_1.28.4
## [11] gridBase_0.4-7 digest_0.6.27
## [13] foreach_1.5.1 htmltools_0.5.1.1
## [13] foreach_1.5.1 htmltools_0.5.2
## [15] fansi_0.5.0 memoise_2.0.0
## [17] magrittr_2.0.1 cluster_2.1.2
## [19] tzdb_0.1.1 Biostrings_2.58.0
## [21] annotate_1.68.0 modelr_0.1.8
## [23] matrixStats_0.59.0 svglite_2.0.0
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## [27] rvest_1.0.0 haven_2.4.1
## [29] xfun_0.24 crayon_1.4.1
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## [33] genefilter_1.72.1 survival_3.2-11
## [19] tzdb_0.1.2 Biostrings_2.60.2
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## [23] matrixStats_0.61.0 svglite_2.0.0
## [25] colorspace_2.0-2 blob_1.2.2
## [27] rvest_1.0.1 haven_2.4.3
## [29] xfun_0.25 crayon_1.4.1
## [31] RCurl_1.98-1.4 jsonlite_1.7.2
## [33] genefilter_1.74.0 survival_3.2-13
## [35] iterators_1.0.13 glue_1.4.2
## [37] gtable_0.3.0 zlibbioc_1.36.0
## [39] XVector_0.30.0 webshot_0.5.2
## [41] DelayedArray_0.16.3 car_3.0-11
## [43] Rhdf5lib_1.12.1 BiocGenerics_0.36.1
## [37] gtable_0.3.0 zlibbioc_1.38.0
## [39] XVector_0.32.0 webshot_0.5.2
## [41] DelayedArray_0.18.0 car_3.0-11
## [43] Rhdf5lib_1.14.2 BiocGenerics_0.38.0
## [45] abind_1.4-5 DBI_1.1.1
## [47] rstatix_0.7.0 Rcpp_1.0.6
## [47] rstatix_0.7.0 Rcpp_1.0.7
## [49] viridisLite_0.4.0 xtable_1.8-4
## [51] bit_4.0.4 foreign_0.8-81
## [53] stats4_4.0.3 htmlwidgets_1.5.3
## [53] stats4_4.1.1 htmlwidgets_1.5.4
## [55] httr_1.4.2 RColorBrewer_1.1-2
## [57] ellipsis_0.3.2 XML_3.99-0.6
## [59] pkgconfig_2.0.3 farver_2.1.0
## [57] ellipsis_0.3.2 pkgconfig_2.0.3
## [59] XML_3.99-0.8 farver_2.1.0
## [61] sass_0.4.0 dbplyr_2.1.1
## [63] locfit_1.5-9.4 utf8_1.2.1
## [65] AnnotationDbi_1.52.0 tidyselect_1.1.1
## [63] locfit_1.5-9.4 utf8_1.2.2
## [65] AnnotationDbi_1.54.1 tidyselect_1.1.1
## [67] labeling_0.4.2 rlang_0.4.11
## [69] cachem_1.0.5 munsell_0.5.0
## [71] cellranger_1.1.0 tools_4.0.3
## [73] cli_3.0.1 RSQLite_2.2.7
## [69] cachem_1.0.6 munsell_0.5.0
## [71] cellranger_1.1.0 tools_4.1.1
## [73] cli_3.0.1 RSQLite_2.2.8
## [75] generics_0.1.0 ade4_1.7-17
## [77] broom_0.7.8 fastmap_1.1.0
## [79] evaluate_0.14 yaml_2.2.1
## [77] broom_0.7.9 evaluate_0.14
## [79] fastmap_1.1.0 yaml_2.2.1
## [81] bit64_4.0.5 knitr_1.33
## [83] fs_1.5.0 zip_2.2.0
## [85] nlme_3.1-152 xml2_1.3.2
## [87] compiler_4.0.3 rstudioapi_0.13
## [89] curl_4.3.2 ggsignif_0.6.2
## [91] reprex_2.0.0 geneplotter_1.68.0
## [93] bslib_0.2.5.1 stringi_1.7.3
## [95] highr_0.9 Matrix_1.3-4
## [97] multtest_2.46.0 vctrs_0.3.8
## [99] pillar_1.6.1 lifecycle_1.0.0
## [101] rhdf5filters_1.2.1 jquerylib_0.1.4
## [103] bitops_1.0-7 GenomicRanges_1.42.0
## [105] R6_2.5.0 rio_0.5.27
## [107] IRanges_2.24.1 codetools_0.2-18
## [109] MASS_7.3-54 assertthat_0.2.1
## [111] rhdf5_2.34.0 SummarizedExperiment_1.20.0
## [113] DESeq2_1.30.1 withr_2.4.2
## [115] S4Vectors_0.28.1 GenomeInfoDbData_1.2.4
## [117] mgcv_1.8-36 hms_1.1.0
## [119] grid_4.0.3 rmarkdown_2.9
## [121] MatrixGenerics_1.2.1 carData_3.0-4
## [123] Biobase_2.50.0 lubridate_1.7.10</code></pre>
## [85] KEGGREST_1.32.0 nlme_3.1-152
## [87] xml2_1.3.2 compiler_4.1.1
## [89] rstudioapi_0.13 png_0.1-7
## [91] curl_4.3.2 ggsignif_0.6.3
## [93] reprex_2.0.1 geneplotter_1.70.0
## [95] bslib_0.3.0 stringi_1.7.4
## [97] highr_0.9 Matrix_1.3-4
## [99] multtest_2.48.0 vctrs_0.3.8
## [101] pillar_1.6.2 lifecycle_1.0.0
## [103] rhdf5filters_1.4.0 jquerylib_0.1.4
## [105] bitops_1.0-7 GenomicRanges_1.44.0
## [107] R6_2.5.1 rio_0.5.27
## [109] IRanges_2.26.0 codetools_0.2-18
## [111] MASS_7.3-54 assertthat_0.2.1
## [113] rhdf5_2.36.0 SummarizedExperiment_1.22.0
## [115] DESeq2_1.32.0 withr_2.4.2
## [117] S4Vectors_0.30.0 GenomeInfoDbData_1.2.6
## [119] mgcv_1.8-36 hms_1.1.0
## [121] grid_4.1.1 rmarkdown_2.11
## [123] MatrixGenerics_1.4.3 carData_3.0-4
## [125] Biobase_2.52.0 lubridate_1.7.10</code></pre>
</div>
</div>
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