text: user-1: I have created a DESeq object (dds) and now I want to access the results and apply the lfc shrinkage on them.
  res <- results(dds, alpha=0.05)
  resultsNames(dds) 
  [1] "Intercept"                                                  "Cell_type_Interstitial_macrophages_vs_Alveolar_macrophages"
  [3] "Cell_type_T_cells_vs_Alveolar_macrophages"
  
  Here we see all the coefficients I got from the results function.
  Now I try to use the lfcShrink() function on the second coefficient:
  res_im_vs_am <- lfcShrink(dds, coef=2, res=res, type="apeglm")
  Error in lfcShrink(dds, coef = 2, res = res, type = "apeglm") : 
    'coef' should specify same coefficient as in results 'res'
  
  it doesn't work, so I try with the name directly copy-pasted from the above code:
  res_im_vs_am <- lfcShrink(dds, coef = "Cell_type_Interstitial_macrophages_vs_Alveolar_macrophages", res=res, type="apeglm")
  Error in lfcShrink(dds, coef = "Cell_type_Interstitial_macrophages_vs_Alveolar_macrophages",  : 
    'coef' should specify same coefficient as in results 'res'    
  
  Same error.
  According to the ?lfcShrink for coef: the name or number of the coefficient (LFC) to shrink, consult resultsNames(dds) after running DESeq(dds).
  So I do not understand why it is not working. Anyone can help?
  
  user5077: We use an example dataset:
  library(DESeq2)
  mat = matrix(rnbinom(9000,mu=100,size=1),ncol=9)
  rownames(mat) = paste0("gene",1:1000)
  grps = rep(c("A","B","C"),each=3)
  
  dds = DESeqDataSetFromMatrix(mat,data.frame(grps),~grps)
  dds = DESeq(dds)
  
  resultsNames(dds) 
  [1] "Intercept"   "grps_B_vs_A" "grps_C_vs_A"
  
  When you call results, by default it takes the last coefficient, in this example is C vs A:
  res <- results(dds, alpha=0.05)
  
  log2 fold change (MLE): grps C vs A 
  Wald test p-value: grps C vs A 
  DataFrame with 6 rows and 6 columns
                baseMean     log2FoldChange             lfcSE               stat
               <numeric>          <numeric>         <numeric>          <numeric>
  gene1 74.3974631643997 -0.439258650876538  1.22842645044656 -0.357578307367818
  gene2 99.4576039995999    1.2903547180366  1.12500005531808   1.14698191518912
  gene3 87.1593850381565  -3.11763876685787  1.19848628038255  -2.60131368868297
  gene4   51.47821785473  -2.16622171024749 0.953571440023498  -2.27169315200349
  gene5 62.4630151830988   1.05879388186169  1.31999477669387  0.802119751195993
  gene6 111.967714581788  -1.23916751032406  1.17612862134365  -1.05359863524824
  
  If you want to look at the second comparison:
  res <- results(dds, alpha=0.05,name="grps_B_vs_A")
  res_lfc <- lfcShrink(dds, coef=2, res=res, type="apeglm")
  
  log2 fold change (MAP): grps B vs A 
  Wald test p-value: grps B vs A 
  DataFrame with 6 rows and 5 columns
                baseMean      log2FoldChange             lfcSE            pvalue
               <numeric>           <numeric>         <numeric>         <numeric>
  gene1 74.3974631643997 0.00143892076074213 0.275057978370776 0.987946388824352
  gene2 99.4576039995999  -0.031292774512063 0.276439771853046 0.632995722892249
  gene3 87.1593850381565 0.00806769808245902 0.274672487627629                NA
  gene4   51.47821785473 -0.0394804572502463 0.274244572145665 0.609999235800452
  gene5 62.4630151830988   0.065875708916621 0.288411208595865 0.234448669110134
  gene6 111.967714581788 -0.0871847461207727 0.295733383995144 0.153081913500716
  
  or simply:
  res_lfc <- lfcShrink(dds, coef=2, type="apeglm")
  
  
original_text: -1: <p>I have created a DESeq object (dds) and now I want to access the results and apply the lfc shrinkage on them.</p>
  <pre><code>res &lt;- results(dds, alpha=0.05)
  resultsNames(dds) 
  [1] &quot;Intercept&quot;                                                  &quot;Cell_type_Interstitial_macrophages_vs_Alveolar_macrophages&quot;
  [3] &quot;Cell_type_T_cells_vs_Alveolar_macrophages&quot;
  </code></pre>
  <p>Here we see all the coefficients I got from the results function.
  Now I try to use the lfcShrink() function on the second coefficient:</p>
  <pre><code>res_im_vs_am &lt;- lfcShrink(dds, coef=2, res=res, type=&quot;apeglm&quot;)
  Error in lfcShrink(dds, coef = 2, res = res, type = &quot;apeglm&quot;) : 
    'coef' should specify same coefficient as in results 'res'
  </code></pre>
  <p>it doesn't work, so I try with the name directly copy-pasted from the above code:</p>
  <pre><code>res_im_vs_am &lt;- lfcShrink(dds, coef = &quot;Cell_type_Interstitial_macrophages_vs_Alveolar_macrophages&quot;, res=res, type=&quot;apeglm&quot;)
  Error in lfcShrink(dds, coef = &quot;Cell_type_Interstitial_macrophages_vs_Alveolar_macrophages&quot;,  : 
    'coef' should specify same coefficient as in results 'res'    
  </code></pre>
  <p>Same error.
  According to the <code>?lfcShrink</code> for coef: the name or number of the coefficient (LFC) to shrink, consult resultsNames(dds) after running DESeq(dds).</p>
  <p>So I do not understand why it is not working. Anyone can help?</p>
   5077: <p>We use an example dataset:</p>
  <pre><code>library(DESeq2)
  mat = matrix(rnbinom(9000,mu=100,size=1),ncol=9)
  rownames(mat) = paste0(&quot;gene&quot;,1:1000)
  grps = rep(c(&quot;A&quot;,&quot;B&quot;,&quot;C&quot;),each=3)
  
  dds = DESeqDataSetFromMatrix(mat,data.frame(grps),~grps)
  dds = DESeq(dds)
  
  resultsNames(dds) 
  [1] &quot;Intercept&quot;   &quot;grps_B_vs_A&quot; &quot;grps_C_vs_A&quot;
  </code></pre>
  <p>When you call <code>results</code>, by default it takes the last coefficient, in this example is C vs A:</p>
  <pre><code>res &lt;- results(dds, alpha=0.05)
  
  log2 fold change (MLE): grps C vs A 
  Wald test p-value: grps C vs A 
  DataFrame with 6 rows and 6 columns
                baseMean     log2FoldChange             lfcSE               stat
               &lt;numeric&gt;          &lt;numeric&gt;         &lt;numeric&gt;          &lt;numeric&gt;
  gene1 74.3974631643997 -0.439258650876538  1.22842645044656 -0.357578307367818
  gene2 99.4576039995999    1.2903547180366  1.12500005531808   1.14698191518912
  gene3 87.1593850381565  -3.11763876685787  1.19848628038255  -2.60131368868297
  gene4   51.47821785473  -2.16622171024749 0.953571440023498  -2.27169315200349
  gene5 62.4630151830988   1.05879388186169  1.31999477669387  0.802119751195993
  gene6 111.967714581788  -1.23916751032406  1.17612862134365  -1.05359863524824
  </code></pre>
  <p>If you want to look at the second comparison:</p>
  <pre><code>res &lt;- results(dds, alpha=0.05,name=&quot;grps_B_vs_A&quot;)
  res_lfc &lt;- lfcShrink(dds, coef=2, res=res, type=&quot;apeglm&quot;)
  
  log2 fold change (MAP): grps B vs A 
  Wald test p-value: grps B vs A 
  DataFrame with 6 rows and 5 columns
                baseMean      log2FoldChange             lfcSE            pvalue
               &lt;numeric&gt;           &lt;numeric&gt;         &lt;numeric&gt;         &lt;numeric&gt;
  gene1 74.3974631643997 0.00143892076074213 0.275057978370776 0.987946388824352
  gene2 99.4576039995999  -0.031292774512063 0.276439771853046 0.632995722892249
  gene3 87.1593850381565 0.00806769808245902 0.274672487627629                NA
  gene4   51.47821785473 -0.0394804572502463 0.274244572145665 0.609999235800452
  gene5 62.4630151830988   0.065875708916621 0.288411208595865 0.234448669110134
  gene6 111.967714581788 -0.0871847461207727 0.295733383995144 0.153081913500716
  </code></pre>
  <p>or simply:</p>
  <pre><code>res_lfc &lt;- lfcShrink(dds, coef=2, type=&quot;apeglm&quot;)
  </code></pre>
  