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<h1 class="title toc-ignore">Analyses 16s projet Obésité 2018</h1>
<h4 class="author">Magali Monnoye</h4>
<address class="author_afil">
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INRAE - MICALIS<br><h4 class="date">2021-11-22 (Last updated: 2022-01-13)</h4>
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</div>


<div id="metagenomic-phyloseq-analysis" class="section level1">
<h1>Metagenomic phyloseq analysis</h1>
<div id="import-packages-et-données" class="section level2">
<h2>Import packages et données</h2>
<p>J’importe les données</p>
<p>Je dispose de l’object phyloseq suivant:</p>
<pre class="r"><code>frogs.data</code></pre>
<pre><code>## phyloseq-class experiment-level object
## otu_table()   OTU Table:         [ 241 taxa and 30 samples ]
## sample_data() Sample Data:       [ 30 samples by 2 sample variables ]
## tax_table()   Taxonomy Table:    [ 241 taxa by 7 taxonomic ranks ]</code></pre>
<p>qui contient les métadonnées suivantes:</p>
<pre class="r"><code>sample_variables(frogs.data)</code></pre>
<pre><code>## [1] &quot;Name&quot;  &quot;Group&quot;</code></pre>
<ul>
<li>Nombre d’échantillons par groupe:</li>
</ul>
<pre class="r"><code>table(get_variable(frogs.data, &quot;Group&quot;))</code></pre>
<pre><code>## 
##   HFD-AB  HFD-H2O STDD-H2O 
##       10       10       10</code></pre>
</div>
<div id="visualisation-de-labondance-par-échantillon" class="section level2 tabset">
<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_Obesite_files/figure-html/01-plot%20abondances-1.png" width="1008" /></p>
</div>
<div id="abondances-niveau-phylum" class="section level3">
<h3>Abondances niveau Phylum</h3>
<p><img src="report_Obesite_files/figure-html/02-plot%20abondances%20phylum-1.png" width="1008" /></p>
</div>
</div>
<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 class="tabset">Représentation des communautés au niveau Phylum</h3>
<ul>
<li>Nombre d’OTUs par Phylum:</li>
</ul>
<pre><code>## 
## Actinobacteria  Bacteroidetes     Firmicutes Proteobacteria 
##              3             29            205              4</code></pre>
<div id="tableaux-relatives-abondances-phylum" class="section level4">
<h4>Tableaux relatives abondances Phylum</h4>
<ul>
<li>Relatives Abondances par échantillons:</li>
</ul>
<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>
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<ul>
<li>Relatives abondances par groupes:</li>
</ul>
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</div>
<div id="plot-composition-phylum" class="section level4">
<h4>Plot composition Phylum</h4>
<p><img src="report_Obesite_files/figure-html/03-composition-phylum-1.png" width="960" /></p>
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<p><img src="report_Obesite_files/figure-html/03bis-composition-phylum-1.png" width="960" /></p>
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<p><img src="report_Obesite_files/figure-html/04-composition-phylum-merged-1.png" width="576" /></p>
</div>
<div id="stats-phylum" class="section level4">
<h4>Stats Phylum</h4>
<div id="boxplot-phylum-avec-stats" class="section level5">
<h5>Boxplot Phylum avec stats</h5>
<p>On va se focaliser sur les 4 Phylums et représenter leurs abondances dans les différents groupe sous forme de boxplot.</p>
<p>Le nombre d’étoiles codent le niveau de significativité, les comparaisons non-significatives ne sont pas indiqués</p>
<div class="alert alert-info" role="alert">
Le test wilcox compare STDD-H2O aux autres groupes
</div>
<p><img src="report_Obesite_files/figure-html/05-Phylum%20stats-1.png" width="960" /></p>
</div>
<div id="kruskal-test" class="section level5">
<h5>Kruskal test</h5>
<p>Test de Kruskal (Anova non paramétrique) pour chaque Phylum pour tester si les abondances sont similaires (pour ce Phylum) entre les différents groupes.</p>
<div data-pagedtable="false">
<script data-pagedtable-source type="application/json">
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  </script>
</div>
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<p><img src="report_Obesite_files/figure-html/figure-phylum%20significatif-1.png" width="960" /></p>
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</div>
</div>
<div id="dunn-post-hoc-test" class="section level4">
<h4>Dunn Post-Hoc test</h4>
<p>Dunn Post-Hoc test sur le résultat Kruskall-Wallis de l’impact de <code>Group</code> sur les abondances Actinobacteriota</p>
<pre><code>## 
##                            Comparison of x by group                            
##                              (Benjamini-Hochberg)                              
## Col Mean-|
## Row Mean |     HFD-AB    HFD-H2O
## ---------+----------------------
##  HFD-H2O |  -2.872619
##          |    0.0031*
##          |
## STDD-H2O |  -4.231290  -1.358671
##          |    0.0000*     0.0871
## 
## alpha = 0.05
## Reject Ho if p &lt;= alpha/2</code></pre>
<p>Dunn Post-Hoc test sur le résultat Kruskall-Wallis de l’impact de <code>Group</code> sur les abondances Bacteroidota</p>
<pre><code>## 
##                            Comparison of x by group                            
##                              (Benjamini-Hochberg)                              
## Col Mean-|
## Row Mean |     HFD-AB    HFD-H2O
## ---------+----------------------
##  HFD-H2O |   4.216404
##          |    0.0000*
##          |
## STDD-H2O |   3.403603  -0.812800
##          |    0.0005*     0.2082
## 
## alpha = 0.05
## Reject Ho if p &lt;= alpha/2</code></pre>
<p>Dunn Post-Hoc test sur le résultat Kruskall-Wallis de l’impact de <code>Group</code> sur les abondances Firmicutes</p>
<pre><code>## 
##                            Comparison of x by group                            
##                              (Benjamini-Hochberg)                              
## Col Mean-|
## Row Mean |     HFD-AB    HFD-H2O
## ---------+----------------------
##  HFD-H2O |  -3.860803
##          |    0.0002*
##          |
## STDD-H2O |  -3.759203   0.101600
##          |    0.0001*     0.4595
## 
## alpha = 0.05
## Reject Ho if p &lt;= alpha/2</code></pre>
<p>Dunn Post-Hoc test sur le résultat Kruskall-Wallis de l’impact de <code>Group</code> sur les abondances Proteobacteria</p>
<pre><code>## 
##                            Comparison of x by group                            
##                              (Benjamini-Hochberg)                              
## Col Mean-|
## Row Mean |     HFD-AB    HFD-H2O
## ---------+----------------------
##  HFD-H2O |  -5.055167
##          |    0.0000*
##          |
## STDD-H2O |  -2.565687   2.489479
##          |    0.0077*    0.0064*
## 
## alpha = 0.05
## Reject Ho if p &lt;= alpha/2</code></pre>
</div>
</div>
<div id="représentation-des-communautés-au-niveau-family" class="section level3 tabset">
<h3 class="tabset">Représentation des communautés au niveau Family</h3>
<ul>
<li>Nombre d’OTUs par Family:</li>
</ul>
<pre><code>## 
##                Alcaligenaceae                Bacteroidaceae 
##                             1                             5 
##     Bacteroidales S24-7 group            Bifidobacteriaceae 
##                            14                             1 
##           Christensenellaceae              Clostridiaceae 1 
##                             2                             1 
## Clostridiales vadinBB60 group             Coriobacteriaceae 
##                             6                             2 
##             Defluviitaleaceae           Desulfovibrionaceae 
##                             1                             2 
##            Enterobacteriaceae               Enterococcaceae 
##                             1                             1 
##           Erysipelotrichaceae                   Family XIII 
##                             4                             2 
##               Lachnospiraceae              Lactobacillaceae 
##                           114                             3 
##         Peptostreptococcaceae            Porphyromonadaceae 
##                             1                             3 
##                Prevotellaceae                 Rikenellaceae 
##                             3                             4 
##               Ruminococcaceae              Streptococcaceae 
##                            69                             1</code></pre>
<div id="tableaux-relatives-abondances-family" class="section level4">
<h4>Tableaux relatives abondances Family</h4>
<ul>
<li>Relative Abondance par échantillon:</li>
</ul>
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class=\"display\">\n  <thead>\n    <tr>\n      <th> <\/th>\n      <th>STD_100<\/th>\n      <th>HFD_10<\/th>\n      <th>STD_172<\/th>\n      <th>ANTIBIO_173<\/th>\n      <th>STD_174<\/th>\n      <th>ANTIBIO_176<\/th>\n      <th>HFD_177<\/th>\n      <th>ANTIBIO_178<\/th>\n      <th>STD_179<\/th>\n      <th>ANTIBIO_180<\/th>\n      <th>ANTIBIO_1<\/th>\n      <th>HFD_2<\/th>\n      <th>HFD_44<\/th>\n      <th>ANTIBIO_47<\/th>\n      <th>STD_50<\/th>\n      <th>HFD_6<\/th>\n      <th>HFD_7<\/th>\n      <th>STD_831<\/th>\n      <th>HFD_832<\/th>\n      <th>ANTIBIO_836<\/th>\n      <th>STD_838<\/th>\n      <th>STD_841<\/th>\n      <th>ANTIBIO_842<\/th>\n      <th>HFD_843<\/th>\n      <th>ANTIBIO_8<\/th>\n      <th>HFD_91<\/th>\n      <th>HFD_94<\/th>\n      <th>STD_97<\/th>\n      <th>STD_99<\/th>\n      <th>ANTIBIO_9<\/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]},{"orderable":false,"targets":0}],"order":[],"autoWidth":false,"orderClasses":false}},"evals":[],"jsHooks":[]}</script>
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<ul>
<li>Relative Abondance par groupe:</li>
</ul>
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<div id="htmlwidget-288e7c7ea23c23eda554" style="width:100%;height:auto;" class="datatables html-widget"></div>
<script type="application/json" data-for="htmlwidget-288e7c7ea23c23eda554">{"x":{"filter":"none","extensions":["Buttons"],"data":[["STDD-H2O","HFD-H2O","HFD-AB"],[13.0689627971197,4.18700220199961,0.0552357432726594],[26.2437889780309,8.02204936774697,0.64117490763942],[2.79911032429428,18.7131204277802,0.0355591015283038],[0.583783863510706,0.00634559404832084,0.00389711613406079],[2.31928828959652,0.199613949293494,0.00427071859438992],[1.79330577633186,2.64183893322244,11.7362951576384],[0.427344342085148,0.246548210529409,0],[5.5659718225113,6.94541703332619,62.4439440847733],[34.9566867452759,20.6741272365103,6.38964602385974],[1.40833171075789,16.5322713645989,14.199053300444],[0.102406607420909,0.447618416843867,0.00366434591425431],[0.159264034502245,0.759112994687504,0.388587804766788],[9.61606150356042,11.9967134878176,0.103638123805737],[0.0615365907684396,3.56210958249433,2.36414874331471],[0.107924847868622,0.123508788277156,0],[0.00244379276637341,0.0402178683382735,0],[0.0634392566818482,0.00627330640634534,0],[0.599711793333464,3.85346720245327,1.45773517727935],[0.0216561169557874,0.913819877543704,0.00448843353619386],[0,0.0132878837528094,0.166483517150237],[0.0298515766872433,0.0535405040915014,0.00217770034843206],[0.0691292299405087,0.0619957682378389,0]],"container":"<table class=\"display\">\n  <thead>\n    <tr>\n      <th> <\/th>\n      <th>Prevotellaceae<\/th>\n      <th>Bacteroidales S24-7 group<\/th>\n      <th>Desulfovibrionaceae<\/th>\n      <th>Bifidobacteriaceae<\/th>\n      <th>Alcaligenaceae<\/th>\n      <th>Bacteroidaceae<\/th>\n      <th>Lactobacillaceae<\/th>\n      <th>Porphyromonadaceae<\/th>\n      <th>Lachnospiraceae<\/th>\n      <th>Rikenellaceae<\/th>\n      <th>Clostridiaceae 1<\/th>\n      <th>Erysipelotrichaceae<\/th>\n      <th>Ruminococcaceae<\/th>\n      <th>Streptococcaceae<\/th>\n      <th>Coriobacteriaceae<\/th>\n      <th>Enterobacteriaceae<\/th>\n      <th>Defluviitaleaceae<\/th>\n      <th>Clostridiales vadinBB60 group<\/th>\n      <th>Peptostreptococcaceae<\/th>\n      <th>Enterococcaceae<\/th>\n      <th>Family XIII<\/th>\n      <th>Christensenellaceae<\/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]},{"orderable":false,"targets":0}],"order":[],"autoWidth":false,"orderClasses":false}},"evals":[],"jsHooks":[]}</script>
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</div>
<div id="plot-composition-family" class="section level4">
<h4>Plot composition Family</h4>
<p><img src="report_Obesite_files/figure-html/06-composition-phylum-1.png" width="960" /></p>
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<p><img src="report_Obesite_files/figure-html/06.2-composition-phylum-1.png" width="960" /></p>
<p><img src="report_Obesite_files/figure-html/06.3-composition-phylum-1.png" width="960" /></p>
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<p><img src="report_Obesite_files/figure-html/07-composition-family%20merged-1.png" width="576" /></p>
</div>
<div id="stats-family" class="section level4">
<h4>Stats Family</h4>
<div id="boxplot-family-avec-stats" class="section level5">
<h5>Boxplot Family avec stats</h5>
<p>On va se focaliser sur les 10 Family et représenter leurs abondances dans les différents groupe sous forme de boxplot.</p>
<p>Le nombre d’étoiles codent le niveau de significativité, les comparaisons non-significatives ne sont pas indiqués</p>
<div class="alert alert-info" role="alert">
Le test wilcox compare STDD-H2O aux autres groupes
</div>
<p><img src="report_Obesite_files/figure-html/08-Family%20stats-1.png" width="1152" /></p>
</div>
<div id="kruskal-test-1" class="section level5">
<h5>Kruskal test</h5>
<p>Test de Kruskal (Anova non paramétrique) pour chaque Family pour tester si les abondances sont similaires (pour la Family) entre les différents groupes.</p>
<div data-pagedtable="false">
<script data-pagedtable-source type="application/json">
{"columns":[{"label":["Family"],"name":[1],"type":["chr"],"align":["left"]},{"label":[".y."],"name":[2],"type":["chr"],"align":["left"]},{"label":["p"],"name":[3],"type":["dbl"],"align":["right"]},{"label":["p.adj"],"name":[4],"type":["dbl"],"align":["right"]},{"label":["p.format"],"name":[5],"type":["chr"],"align":["left"]},{"label":["p.signif"],"name":[6],"type":["chr"],"align":["left"]},{"label":["method"],"name":[7],"type":["chr"],"align":["left"]}],"data":[{"1":"Porphyromonadaceae","2":"Abundance","3":"5.205416e-05","4":"7.3e-04","5":"5.2e-05","6":"****","7":"Kruskal-Wallis"},{"1":"Lachnospiraceae","2":"Abundance","3":"3.283975e-05","4":"5.4e-04","5":"3.3e-05","6":"****","7":"Kruskal-Wallis"},{"1":"Bacteroidales S24-7 group","2":"Abundance","3":"3.624689e-06","4":"7.6e-05","5":"3.6e-06","6":"****","7":"Kruskal-Wallis"},{"1":"Desulfovibrionaceae","2":"Abundance","3":"2.461552e-06","4":"5.4e-05","5":"2.5e-06","6":"****","7":"Kruskal-Wallis"},{"1":"Prevotellaceae","2":"Abundance","3":"1.966362e-05","4":"3.7e-04","5":"2.0e-05","6":"****","7":"Kruskal-Wallis"},{"1":"Rikenellaceae","2":"Abundance","3":"5.362215e-05","4":"7.3e-04","5":"5.4e-05","6":"****","7":"Kruskal-Wallis"},{"1":"Ruminococcaceae","2":"Abundance","3":"3.095119e-05","4":"5.4e-04","5":"3.1e-05","6":"****","7":"Kruskal-Wallis"},{"1":"Bacteroidaceae","2":"Abundance","3":"2.981064e-05","4":"5.4e-04","5":"3.0e-05","6":"****","7":"Kruskal-Wallis"},{"1":"Streptococcaceae","2":"Abundance","3":"7.476676e-05","4":"8.9e-04","5":"7.5e-05","6":"****","7":"Kruskal-Wallis"},{"1":"Clostridiales vadinBB60 group","2":"Abundance","3":"9.309036e-04","4":"5.0e-03","5":"0.00093","6":"***","7":"Kruskal-Wallis"},{"1":"Alcaligenaceae","2":"Abundance","3":"9.327098e-06","4":"1.9e-04","5":"9.3e-06","6":"****","7":"Kruskal-Wallis"},{"1":"Erysipelotrichaceae","2":"Abundance","3":"4.212787e-02","4":"8.4e-02","5":"0.04213","6":"*","7":"Kruskal-Wallis"},{"1":"Peptostreptococcaceae","2":"Abundance","3":"7.454999e-05","4":"8.9e-04","5":"7.5e-05","6":"****","7":"Kruskal-Wallis"},{"1":"Bifidobacteriaceae","2":"Abundance","3":"1.740795e-04","4":"1.7e-03","5":"0.00017","6":"***","7":"Kruskal-Wallis"},{"1":"Lactobacillaceae","2":"Abundance","3":"4.059667e-05","4":"6.1e-04","5":"4.1e-05","6":"****","7":"Kruskal-Wallis"},{"1":"Clostridiaceae 1","2":"Abundance","3":"2.707793e-03","4":"8.1e-03","5":"0.00271","6":"**","7":"Kruskal-Wallis"},{"1":"Enterococcaceae","2":"Abundance","3":"7.508506e-02","4":"8.4e-02","5":"0.07509","6":"ns","7":"Kruskal-Wallis"},{"1":"Coriobacteriaceae","2":"Abundance","3":"2.275302e-04","4":"2.0e-03","5":"0.00023","6":"***","7":"Kruskal-Wallis"},{"1":"Christensenellaceae","2":"Abundance","3":"7.201850e-04","4":"5.0e-03","5":"0.00072","6":"***","7":"Kruskal-Wallis"},{"1":"Enterobacteriaceae","2":"Abundance","3":"1.146023e-03","4":"5.0e-03","5":"0.00115","6":"**","7":"Kruskal-Wallis"},{"1":"Family XIII","2":"Abundance","3":"7.799492e-04","4":"5.0e-03","5":"0.00078","6":"***","7":"Kruskal-Wallis"},{"1":"Defluviitaleaceae","2":"Abundance","3":"2.864253e-04","4":"2.3e-03","5":"0.00029","6":"***","7":"Kruskal-Wallis"}],"options":{"columns":{"min":{},"max":[10]},"rows":{"min":[10],"max":[10]},"pages":{}}}
  </script>
</div>
</div>
</div>
<div id="dunn-post-hoc-test-1" class="section level4">
<h4>Dunn Post-Hoc test</h4>
<p>Dunn Post-Hoc test sur le résultat Kruskall-Wallis de l’impact de <code>Group</code> sur les abondances Bacteroidaceae</p>
<pre><code>## 
##                            Comparison of x by group                            
##                              (Benjamini-Hochberg)                              
## Col Mean-|
## Row Mean |     HFD-AB    HFD-H2O
## ---------+----------------------
##  HFD-H2O |   3.200403
##          |    0.0010*
##          |
## STDD-H2O |   4.419604   1.219201
##          |    0.0000*     0.1114
## 
## alpha = 0.05
## Reject Ho if p &lt;= alpha/2</code></pre>
<p>Dunn Post-Hoc test sur le résultat Kruskall-Wallis de l’impact de <code>Group</code> sur les abondances Bacteroidales S24-7 group</p>
<pre><code>## 
##                            Comparison of x by group                            
##                              (Benjamini-Hochberg)                              
## Col Mean-|
## Row Mean |     HFD-AB    HFD-H2O
## ---------+----------------------
##  HFD-H2O |  -2.616202
##          |    0.0067*
##          |
## STDD-H2O |  -5.003805  -2.387602
##          |    0.0000*    0.0085*
## 
## alpha = 0.05
## Reject Ho if p &lt;= alpha/2</code></pre>
<p>Dunn Post-Hoc test sur le résultat Kruskall-Wallis de l’impact de <code>Group</code> sur les abondances Clostridiales vadinBB60 group</p>
<pre><code>## 
##                            Comparison of x by group                            
##                              (Benjamini-Hochberg)                              
## Col Mean-|
## Row Mean |     HFD-AB    HFD-H2O
## ---------+----------------------
##  HFD-H2O |  -1.752601
##          |     0.0398
##          |
## STDD-H2O |   1.981201   3.733803
##          |     0.0357    0.0003*
## 
## alpha = 0.05
## Reject Ho if p &lt;= alpha/2</code></pre>
<p>Dunn Post-Hoc test sur le résultat Kruskall-Wallis de l’impact de <code>Group</code> sur les abondances Desulfovibrionaceae</p>
<pre><code>## 
##                            Comparison of x by group                            
##                              (Benjamini-Hochberg)                              
## Col Mean-|
## Row Mean |     HFD-AB    HFD-H2O
## ---------+----------------------
##  HFD-H2O |  -5.082266
##          |    0.0000*
##          |
## STDD-H2O |  -2.541133   2.541133
##          |    0.0055*    0.0083*
## 
## alpha = 0.05
## Reject Ho if p &lt;= alpha/2</code></pre>
<p>Dunn Post-Hoc test sur le résultat Kruskall-Wallis de l’impact de <code>Group</code> sur les abondances Lachnospiraceae</p>
<pre><code>## 
##                            Comparison of x by group                            
##                              (Benjamini-Hochberg)                              
## Col Mean-|
## Row Mean |     HFD-AB    HFD-H2O
## ---------+----------------------
##  HFD-H2O |  -2.819402
##          |    0.0036*
##          |
## STDD-H2O |  -4.495804  -1.676401
##          |    0.0000*     0.0468
## 
## alpha = 0.05
## Reject Ho if p &lt;= alpha/2</code></pre>
<p>Dunn Post-Hoc test sur le résultat Kruskall-Wallis de l’impact de <code>Group</code> sur les abondances Porphyromonadaceae</p>
<pre><code>## 
##                            Comparison of x by group                            
##                              (Benjamini-Hochberg)                              
## Col Mean-|
## Row Mean |     HFD-AB    HFD-H2O
## ---------+----------------------
##  HFD-H2O |   3.505203
##          |    0.0003*
##          |
## STDD-H2O |   4.114804   0.609600
##          |    0.0001*     0.2711
## 
## alpha = 0.05
## Reject Ho if p &lt;= alpha/2</code></pre>
<p>Dunn Post-Hoc test sur le résultat Kruskall-Wallis de l’impact de <code>Group</code> sur les abondances Prevotellaceae</p>
<pre><code>## 
##                            Comparison of x by group                            
##                              (Benjamini-Hochberg)                              
## Col Mean-|
## Row Mean |     HFD-AB    HFD-H2O
## ---------+----------------------
##  HFD-H2O |  -2.515722
##          |    0.0089*
##          |
## STDD-H2O |  -4.650274  -2.134552
##          |    0.0000*    0.0164*
## 
## alpha = 0.05
## Reject Ho if p &lt;= alpha/2</code></pre>
<p>Dunn Post-Hoc test sur le résultat Kruskall-Wallis de l’impact de <code>Group</code> sur les abondances Rikenellaceae</p>
<pre><code>## 
##                            Comparison of x by group                            
##                              (Benjamini-Hochberg)                              
## Col Mean-|
## Row Mean |     HFD-AB    HFD-H2O
## ---------+----------------------
##  HFD-H2O |  -0.558800
##          |     0.2881
##          |
## STDD-H2O |   3.530603   4.089404
##          |    0.0003*    0.0001*
## 
## alpha = 0.05
## Reject Ho if p &lt;= alpha/2</code></pre>
<p>Dunn Post-Hoc test sur le résultat Kruskall-Wallis de l’impact de <code>Group</code> sur les abondances Ruminococcaceae</p>
<pre><code>## 
##                            Comparison of x by group                            
##                              (Benjamini-Hochberg)                              
## Col Mean-|
## Row Mean |     HFD-AB    HFD-H2O
## ---------+----------------------
##  HFD-H2O |  -4.399100
##          |    0.0000*
##          |
## STDD-H2O |  -3.229397   1.169703
##          |    0.0009*     0.1211
## 
## alpha = 0.05
## Reject Ho if p &lt;= alpha/2</code></pre>
<p>Dunn Post-Hoc test sur le résultat Kruskall-Wallis de l’impact de <code>Group</code> sur les abondances Streptococcaceae</p>
<pre><code>## 
##                            Comparison of x by group                            
##                              (Benjamini-Hochberg)                              
## Col Mean-|
## Row Mean |     HFD-AB    HFD-H2O
## ---------+----------------------
##  HFD-H2O |  -0.610279
##          |     0.2708
##          |
## STDD-H2O |   3.432824   4.043103
##          |    0.0004*    0.0001*
## 
## alpha = 0.05
## Reject Ho if p &lt;= alpha/2</code></pre>
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<p>Dunn Post-Hoc test sur le résultat Kruskall-Wallis de l’impact de <code>Group</code> sur les abondances Erysipelotrichaceae</p>
<pre><code>## 
##                            Comparison of x by group                            
##                              (Benjamini-Hochberg)                              
## Col Mean-|
## Row Mean |     HFD-AB    HFD-H2O
## ---------+----------------------
##  HFD-H2O |  -0.177998
##          |     0.4294
##          |
## STDD-H2O |   2.085122   2.263121
##          |     0.0278     0.0354
## 
## alpha = 0.05
## Reject Ho if p &lt;= alpha/2</code></pre>
<p>Dunn Post-Hoc test sur le résultat Kruskall-Wallis de l’impact de <code>Group</code> sur les abondances Bifidobacteriaceae</p>
<pre><code>## 
##                            Comparison of x by group                            
##                              (Benjamini-Hochberg)                              
## Col Mean-|
## Row Mean |     HFD-AB    HFD-H2O
## ---------+----------------------
##  HFD-H2O |  -0.329803
##          |     0.3708
##          |
## STDD-H2O |  -3.756895  -3.427091
##          |    0.0003*    0.0005*
## 
## alpha = 0.05
## Reject Ho if p &lt;= alpha/2</code></pre>
<p>Dunn Post-Hoc test sur le résultat Kruskall-Wallis de l’impact de <code>Group</code> sur les abondances Coriobacteriaceae</p>
<pre><code>## 
##                            Comparison of x by group                            
##                              (Benjamini-Hochberg)                              
## Col Mean-|
## Row Mean |     HFD-AB    HFD-H2O
## ---------+----------------------
##  HFD-H2O |  -3.635459
##          |    0.0004*
##          |
## STDD-H2O |  -3.451717   0.183741
##          |    0.0004*     0.4271
## 
## alpha = 0.05
## Reject Ho if p &lt;= alpha/2</code></pre>
<p>Dunn Post-Hoc test sur le résultat Kruskall-Wallis de l’impact de <code>Group</code> sur les abondances Alcaligenaceae</p>
<pre><code>## 
##                            Comparison of x by group                            
##                              (Benjamini-Hochberg)                              
## Col Mean-|
## Row Mean |     HFD-AB    HFD-H2O
## ---------+----------------------
##  HFD-H2O |  -1.966838
##          |    0.0246*
##          |
## STDD-H2O |  -4.787698  -2.820860
##          |    0.0000*    0.0036*
## 
## alpha = 0.05
## Reject Ho if p &lt;= alpha/2</code></pre>
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</div>
</div>
<div id="zoom-au-niveau-family-dans-chacun-des-phylums" class="section level3 tabset">
<h3 class="tabset">Zoom au niveau Family dans chacun des Phylums</h3>
<p>Les 4 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>
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<p><img src="report_Obesite_files/figure-html/09-composition-Actinobacteriota-1.png" width="864" /></p>
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<p><img src="report_Obesite_files/figure-html/10-composition-Actinobacteriota%20merged-1.png" width="576" /></p>
</div>
<div id="bacteroidota" class="section level4">
<h4>Bacteroidota</h4>
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<p><img src="report_Obesite_files/figure-html/11-composition-bacteroidetes-1.png" width="864" /></p>
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<p><img src="report_Obesite_files/figure-html/12-composition-Bacteroidota%20merged-1.png" width="576" /></p>
</div>
<div id="firmicutes" class="section level4">
<h4>Firmicutes</h4>
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<p><img src="report_Obesite_files/figure-html/17-composition-firmicutes-1.png" width="864" /></p>
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<p><img src="report_Obesite_files/figure-html/18-composition-Firmicutes%20merged-1.png" width="576" /></p>
</div>
<div id="proteobacteria" class="section level4">
<h4>Proteobacteria</h4>
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<p><img src="report_Obesite_files/figure-html/19-composition-proteobacteria-1.png" width="864" /></p>
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<p><img src="report_Obesite_files/figure-html/20-composition-Proteobacteria%20merged-1.png" width="576" /></p>
</div>
</div>
</div>
<div id="diversité-alpha" class="section level2">
<h2>Diversité <span class="math inline">\(\alpha\)</span></h2>
<div id="courbes-de-raréfaction" class="section level3">
<h3>Courbes de raréfaction</h3>
<p>Comme ces distances sont sensibles à la profondeur d’échantillonnage, on va raréfier les échantillons avant de calculer les distances.</p>
<p>Normalisation par rarefaction: même nombre de séquences pour chaque échantillon.</p>
<pre class="r"><code>#On peut rajouter le filtre sur l&#39;abondance &gt;= 10000
#abundant.samples &lt;- (sample_sums(frogs.data) &gt;= 10000) 
#frogs.data.rare &lt;- rarefy_even_depth(prune_samples(abundant.samples, frogs.data), rngseed = 20170317)

frogs.data.rare&lt;-rarefy_even_depth(frogs.data,rngseed=20170329)
sample_sums(frogs.data.rare)[1:5]</code></pre>
<pre><code>##     STD_100      HFD_10     STD_172 ANTIBIO_173     STD_174 
##        3640        3640        3640        3640        3640</code></pre>
<p>Avant de calculer les diversités <span class="math inline">\(\alpha\)</span>, on va faire des courbes de raréfaction pour vérifier si on a saturé la richesse sous-dominante (i.e. celle qui passe les filtres d’abondances).</p>
<p><img src="report_Obesite_files/figure-html/21-ggrare-1.png" width="960" /></p>
</div>
<div id="effet-du-régime-sur-la-diversité" class="section level3">
<h3>Effet du régime sur la diversité</h3>
<p>alpha diversité: Diversité au sein d’un échantillon / Une valeur par échantillon</p>
<div class="alert alert-info" role="alert">
<ul>
<li><p><strong>OBSERVED</strong>: compte le nombre d’OTU observés dans chaque echantillon.</p></li>
<li><p><strong>CHAO1</strong>: Nb d’OTU + Nb d’OTU que l’on a pas vu, applique des corrections pour prendre en compte la diversité.</p></li>
<li><p><strong>SHANNON</strong>: sensible aux variations d’importance des espèces les plus RARES / la valeur de la fonction de Shannon augmente avec la diversité</p>
<ul>
<li><p>Shannon minimal -&gt; Diversité la plus faible, tous les individus de la population sont de la même espèce (ou une seule espèce est sur-représentée alors que toutes les autres ne contiennent qu’un seul individu).</p></li>
<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>
<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_Obesite_files/figure-html/22-plot-richness-1.png" width="672" /></p>
</div>
<div id="richness-table" class="section level3">
<h3>Richness Table</h3>
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<div id="htmlwidget-b4636977310bbc024c51" style="width:100%;height:auto;" class="datatables html-widget"></div>
<script type="application/json" data-for="htmlwidget-b4636977310bbc024c51">{"x":{"filter":"none","extensions":["Buttons"],"data":[["STD_100","HFD_10","STD_172","ANTIBIO_173","STD_174","ANTIBIO_176","HFD_177","ANTIBIO_178","STD_179","ANTIBIO_180","ANTIBIO_1","HFD_2","HFD_44","ANTIBIO_47","STD_50","HFD_6","HFD_7","STD_831","HFD_832","ANTIBIO_836","STD_838","STD_841","ANTIBIO_842","HFD_843","ANTIBIO_8","HFD_91","HFD_94","STD_97","STD_99","ANTIBIO_9"],[152,138,172,27,167,29,140,17,155,35,34,135,125,14,157,146,123,174,142,49,146,130,34,118,25,129,131,144,169,27],[3.39694026800998,3.33829494407201,3.73906609083982,1.27967883887018,3.82364627573542,1.41307066534863,3.66659412255253,1.20796797858404,3.52271901848078,1.59298445258942,1.38264616760762,3.42960483871266,3.11994255179459,1.47142977453773,3.75199664409985,3.48309873295785,2.84623069101291,3.92121342966139,3.62939657171348,1.31242009337339,3.43387181432165,3.15254186820687,1.25159783080388,3.56015817235238,1.57819518322084,3.32499518137019,3.46069431376318,3.63347516674121,3.89164811944472,1.39213446217087],[10.572441696595,10.9436001379989,18.1225590226631,2.25452755708168,21.9735800515853,2.51130382296137,23.0575259501632,2.03083184804441,16.3785423288466,2.94678190327008,2.46460817132143,11.9364339275225,9.48149526396693,2.63121208632419,19.8939063534519,12.1358394599969,5.80592367560094,23.2680610384699,21.9000983247338,2.11828714847012,12.1494164754165,12.2438093048244,2.27384793623678,20.2263153021151,2.76458025007505,12.9910185472456,16.4072964706114,18.4638195758628,23.5138237483298,2.48048357447237],["STD_100","HFD_10","STD_172","ANTIBIO_173","STD_174","ANTIBIO_176","HFD_177","ANTIBIO_178","STD_179","ANTIBIO_180","ANTIBIO_1","HFD_2","HFD_44","ANTIBIO_47","STD_50","HFD_6","HFD_7","STD_831","HFD_832","ANTIBIO_836","STD_838","STD_841","ANTIBIO_842","HFD_843","ANTIBIO_8","HFD_91","HFD_94","STD_97","STD_99","ANTIBIO_9"],["STDD-H2O","HFD-H2O","STDD-H2O","HFD-AB","STDD-H2O","HFD-AB","HFD-H2O","HFD-AB","STDD-H2O","HFD-AB","HFD-AB","HFD-H2O","HFD-H2O","HFD-AB","STDD-H2O","HFD-H2O","HFD-H2O","STDD-H2O","HFD-H2O","HFD-AB","STDD-H2O","STDD-H2O","HFD-AB","HFD-H2O","HFD-AB","HFD-H2O","HFD-H2O","STDD-H2O","STDD-H2O","HFD-AB"],[4092,5165,4485,4215,4079,5458,4633,4996,3849,5402,5132,5096,4458,4901,4171,5012,5163,4053,4836,4592,4717,4115,4726,3854,4407,4525,4285,3640,4580,5337]],"container":"<table class=\"display\">\n  <thead>\n    <tr>\n      <th> <\/th>\n      <th>Observed<\/th>\n      <th>Shannon<\/th>\n      <th>InvSimpson<\/th>\n      <th>Name<\/th>\n      <th>Group<\/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":[1,2,3,6]},{"orderable":false,"targets":0}],"order":[],"autoWidth":false,"orderClasses":false}},"evals":[],"jsHooks":[]}</script>
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</div>
</div>
<div id="statistiques-sur-la-diversité" class="section level2 tabset">
<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">
<h4>Anova sur la Richness Observed</h4>
<p>Analyse de la variance, compare les moyennes d’échantillons.</p>
<div data-pagedtable="false">
<script data-pagedtable-source type="application/json">
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  </script>
</div>
<p>Df: nombre de degrés de liberté</p>
<p>Sum Sq: inertie inter et intra respectivement</p>
<p>Mean Sq: c’est la variance, obtenue en faisant le quotient de la 2eme colonne par la 1ere (moyenne des inerties)</p>
<p>F value: obtenue en faisant quotient des 2 valeurs trouvées dans la 3eme colonne</p>
<p>Pr(&gt;F): pvalue</p>
</div>
<div id="coefficient-richness-observed" class="section level4">
<h4>Coefficient Richness Observed</h4>
<p>coef function: permet d’extraire que les coefficients estimés, mesure l’écart des groupes à la moyenne.</p>
<p>Groupes équilibrés si les valeurs sont du même ordre de grandeur.</p>
<pre><code>## GroupSTDD-H2O  GroupHFD-H2O   GroupHFD-AB 
##         156.6         132.7          29.1</code></pre>
</div>
<div id="test-de-comparaisons-multiples-sur-richness-observed" class="section level4">
<h4>Test de comparaisons multiples sur Richness Observed</h4>
<p>Utilisé pour déterminer les différences significatives entre les moyennes de groupes dans une analyse de variance.</p>
<p>Pour étudier les différences inter-groupes, permet de distinguer parmi les échantillons s’il y en a qui diffèrent significativement des autres.</p>
<pre><code>##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = Observed ~ 0 + Group, data = div_data)
## 
## $Group
##                    diff        lwr        upr    p adj
## HFD-H2O-STDD-H2O  -23.9  -36.37837  -11.42163 0.000172
## HFD-AB-STDD-H2O  -127.5 -139.97837 -115.02163 0.000000
## HFD-AB-HFD-H2O   -103.6 -116.07837  -91.12163 0.000000</code></pre>
<p>diff: différences entre les moyennes obséervées</p>
<p>lwr et upr: donnent les bornes inférieure et supérieur de l’intervalle</p>
<p>p adj: pvalue après ajustement pour les comparaisons multiples</p>
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  </script>
</div>
<p><img src="report_Obesite_files/figure-html/plot_stats%20observed-1.png" width="192" /></p>
</div>
</div>
<div id="statistiques-sur-richness-shannon" class="section level3">
<h3>Statistiques sur Richness shannon</h3>
<div id="anova-sur-la-richness-shannon" class="section level4">
<h4>Anova sur la Richness Shannon</h4>
<div data-pagedtable="false">
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  </script>
</div>
</div>
<div id="coefficient-shannon" class="section level4">
<h4>Coefficient Shannon</h4>
<pre><code>## GroupSTDD-H2O  GroupHFD-H2O   GroupHFD-AB 
##      3.626712      3.385901      1.388213</code></pre>
</div>
<div id="test-de-comparaisons-multiples-sur-richness-shannon" class="section level4">
<h4>Test de comparaisons multiples sur Richness Shannon</h4>
<pre><code>##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = Shannon ~ 0 + Group, data = div_data)
## 
## $Group
##                        diff        lwr          upr     p adj
## HFD-H2O-STDD-H2O -0.2408109 -0.4800928 -0.001528886 0.0483223
## HFD-AB-STDD-H2O  -2.2384993 -2.4777813 -1.999217353 0.0000000
## HFD-AB-HFD-H2O   -1.9976885 -2.2369704 -1.758406496 0.0000000</code></pre>
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  </script>
</div>
<p><img src="report_Obesite_files/figure-html/plot_stats%20Shannon-1.png" width="192" /></p>
</div>
</div>
<div id="statistiques-sur-richness-invsimpson" class="section level3">
<h3>Statistiques sur Richness InvSimpson</h3>
<div id="anova-sur-la-richness-invsimpson" class="section level4">
<h4>Anova sur la Richness InvSimpson</h4>
<div data-pagedtable="false">
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  </script>
</div>
</div>
<div id="coefficient-invsimpson" class="section level4">
<h4>Coefficient InvSimpson</h4>
<pre><code>## GroupSTDD-H2O  GroupHFD-H2O   GroupHFD-AB 
##     17.657996     14.488555      2.447646</code></pre>
</div>
<div id="test-de-comparaisons-multiples-sur-richness-invsimpson" class="section level4">
<h4>Test de comparaisons multiples sur Richness InvSimpson</h4>
<pre><code>##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = InvSimpson ~ 0 + Group, data = div_data)
## 
## $Group
##                        diff        lwr        upr     p adj
## HFD-H2O-STDD-H2O  -3.169441  -7.916057   1.577174 0.2404944
## HFD-AB-STDD-H2O  -15.210350 -19.956965 -10.463734 0.0000000
## HFD-AB-HFD-H2O   -12.040908 -16.787524  -7.294293 0.0000029</code></pre>
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</div>
<p><img src="report_Obesite_files/figure-html/plot_stats%20InvSimpson-1.png" width="288" /></p>
</div>
</div>
</div>
<div id="diversité-alpha-avec-stats" class="section level2">
<h2>Diversité <span class="math inline">\(\alpha\)</span> avec stats</h2>
<p><img src="report_Obesite_files/figure-html/plot_stats%20combo-1.png" width="576" /></p>
</div>
<div id="diversité-beta" class="section level2">
<h2>Diversité <span class="math inline">\(\beta\)</span></h2>
<p>Diversité entre les communautés, comparaison des échantillons entre eux / les communautés entre elles.</p>
<div class="alert alert-info" role="alert">
<ul>
<li><strong>Bray-Curtis</strong> (dissimilarité) / Info abondance</li>
</ul>
<p>Bray curtis nous permet de visualiser la composition, l’abondance, la dominance, etc… de communautés dans l’écosystème et peut être utilisé pour obtenir un résultat du degré de dissemblance entre les espèces. L’indice de Bray-Curtis donne le même poids aux différences d’abondances observées pour les espèces rares que pour les espèces importantes.</p>
<p>Si =1 cela signifie que les communautés sont totalement différentes.</p>
<ul>
<li><strong>Jaccard</strong> (similarité) / Info présence - absence</li>
</ul>
<p>Cet indice va de 0 → les deux échantillons partagent les mêmes OTUs à 1 → les deux échantillons n’ont aucunOTU en commun</p>
<ul>
<li><p><strong>Unifrac</strong> (phylogénie) prend en compte arbre phylogénique et l’abondance : la distance UniFrac entre deux échantillons se base sur les longueurs des branches de l’arbre partagées entre ces deux échantillons.</p>
<ul>
<li><p>unifrac = 0 pas de branche partagée.</p></li>
<li><p>unifrac = 1 pas de branche partagée.</p></li>
</ul></li>
<li><p><strong>Weighted UniFrac</strong> (pondéré) intègre les abondances lors du calcul des longueurs de branches partagées / non partagées pour calculer la distance.</p></li>
</ul>
<p>UniFrac non pondéré est plus sensible aux différences de caractéristiques de faible abondance.</p>
</div>
<div id="calcul-des-distances" class="section level3">
<h3>Calcul des distances</h3>
<p><img src="report_Obesite_files/figure-html/23-dist-as-heatmap-1.png" width="960" /></p>
</div>
<div id="ordination-des-échantillons" class="section level3 tabset">
<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.
</div>
<div id="plot-ordination-bray-curtis" class="section level4">
<h4>Plot ordination Bray Curtis</h4>
<p><img src="report_Obesite_files/figure-html/24-ord-plot-bray-1.png" width="768" /></p>
<div class="alert alert-info" role="alert">
<p>Pour confirmer l’effet du régime sur les distances, on va faire une permanova.</p>
Analyse multivariée de la variance par permutations basée sur les matrices de distances
</div>
<ul>
<li>Adonis sur la matrice Bray Curtis</li>
</ul>
<pre><code>## 
## Call:
## adonis(formula = dist.bc ~ Group, data = as(sample_data(frogs.data.rare),      &quot;data.frame&quot;)) 
## 
## Permutation: free
## Number of permutations: 999
## 
## Terms added sequentially (first to last)
## 
##           Df SumsOfSqs MeanSqs F.Model      R2 Pr(&gt;F)    
## Group      2    5.7476 2.87379  38.468 0.74023  0.001 ***
## Residuals 27    2.0171 0.07471         0.25977           
## Total     29    7.7646                 1.00000           
## ---
## Signif. codes:  0 &#39;***&#39; 0.001 &#39;**&#39; 0.01 &#39;*&#39; 0.05 &#39;.&#39; 0.1 &#39; &#39; 1</code></pre>
<p>Df: degree of freedom.</p>
<p>Sums Of Sqs: sum of squares.</p>
<p>MeanSqs: sum of squares by degree of freedom.</p>
<p>F: F statistics.</p>
<p>R2: partial R-squared.</p>
<p>Pr(&gt;F) p-value based</p>
</div>
<div id="plot-ordination-jaccard" class="section level4">
<h4>Plot ordination Jaccard</h4>
<p><img src="report_Obesite_files/figure-html/28-ord-plot-jac-1.png" width="768" /></p>
<ul>
<li>Adonis sur la matrice Jaccard</li>
</ul>
<pre><code>## 
## Call:
## adonis(formula = dist.jac ~ Group, data = as(sample_data(frogs.data.rare),      &quot;data.frame&quot;)) 
## 
## Permutation: free
## Number of permutations: 999
## 
## Terms added sequentially (first to last)
## 
##           Df SumsOfSqs MeanSqs F.Model      R2 Pr(&gt;F)    
## Group      2    4.2039 2.10193  17.021 0.55768  0.001 ***
## Residuals 27    3.3343 0.12349         0.44232           
## Total     29    7.5382                 1.00000           
## ---
## Signif. codes:  0 &#39;***&#39; 0.001 &#39;**&#39; 0.01 &#39;*&#39; 0.05 &#39;.&#39; 0.1 &#39; &#39; 1</code></pre>
</div>
</div>
<div id="clustering-des-échantillons" class="section level3 tabset">
<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>
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