title: ANOVA and post-test for expression data in R
body: <p>I have a dataset of expression values from 3 groups (proteome expression data as log2).
  Now I would like to perform first an ANOVA to check for proteins differentially expressed in any of the 3 groups and next perform a post-test (eg Tukeys) to figure out which proteins are affected in which specific group comparison.</p>
  <p>Unfortunately, no resources I found discussed this rather simple case but only much more complicated cases with multiple group combinations (and eg two treatments).</p>
  <p>With the HybridMTest package, the ANOVA went fine and I have now the FDR for differentially expressed proteins between the 3 groups (6 samples per group).
  But now I'm stuck on how to calculate the posttest for every protein (= rows, n = 3878) between all of the 3 groups.</p>
  <p>I could not find an appropriate package or function, maybe one of you could offer a hint on how to solve this? I would like to obtain as a result a df with the protein_id, the comparison group, the FDR and the logFoldChange.</p>
  <p>Many thanks!
  (and sorry for providing the data only in a very descriptive way. I dont know how to create example expression data but will look into it)</p>
  <p>Sebastian</p>
  <hr />
  <p>Data description:</p>
  <p>expression_df:
  rownames(expression_df) = protein_id, colnames(expression_df) = sample_id</p>
  <p>pheno_df:
  rownames(pheno_df) = sample_id, pheno_df$cluster = cluster group (n=3)</p>
  <p>anova_results:
  rownames(protein_id), anova_results$FDR = FDR controlled ANOVA result</p>