Active Layer Taxonomy

Taxa plots of clean 16S OTU tables including survey and experimental samples

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Import clean OTU tables

‘Taxa’ are OTUs

1 Data Overview

• OTU tables rarefied to 1,096 reads / sample
  
• reads from ‘Survey’ and ‘Experiment’ were clustered together (OTUs correspond)
  
• at Domain level, only Bacteria detected
  
• among both datasets, a total of 1,724 unique OTUs detected
  
• only forward reads used

1.1 Survey

• n samples: 74
  
• n OTUs: 1,639
  

1.2 Experiment

• n samples: 55
  
• n OTUs: 1,402
  
  

Set-up taxonomy for plotting

1.3 Global: Calculate mean relative abundance by tax rank and export csv of relative abundance

1.3.1 merge samples within dataset

1.3.2 tax glom and export

(no generating code just copy and replace)

1.4 Samples: Calculate relative abundance by tax rank and export csv of relative abundance

1. create vectors of top 10 taxa names to plot for all ranks

• auto-generated code found:

1. set minimum threshold of 0.5% all-sample (a.k.a global) mean relative abundance - (so that taxa below this threshold won’t get plotted)

2. tax glom by each rank
3. transform to relative abundance
4. psmelt
5. add column “[rank]_all” to preserve names not in top 10
6. recode all taxa not in top 10 to by “LowAbundance” & revalue with specifics later (in dat_Survey.[rank].r and in dat_Exp.[rank].r)

1.4.1 generating code:

Survey.rank.names<-rank_names(Survey)[2:6]
Exp.rank.names<-rank_names(Exp)[2:6] #change 6 to 7 if fungal

#change from survey to exp next

# add this line to beginning
  #  cat('\n # Set min plotting threshold to 0.5% relative abundance (all-sample a.k.a global mean) \n')

#also adding psmelt step

for(rank in Survey.rank.names) {

  cat('\n## \n')

  cat('################## \n')

  cat('# Survey:', rank, '# \n')

  cat('################## \n')

  cat('\n')
  
   cat('min_nname_Survey_', rank, '<-length(unique(Survey_', rank, '_Mean_Abund$', 
       rank, '[Survey_', rank, '_Mean_Abund$Survey_', rank, '_Mean > 0.5]))',
       sep = '')
  
  cat('\n \n ')

    cat('if (min_nname_Survey_', rank, ' < 10){
  Survey.', rank, '.names.to.plot<-top_n(Survey_', rank, '_Mean_Abund, min_nname_Survey_', rank, ', Survey_', rank, '_Mean)$',rank, ' 
} else {
  Survey.', rank, '.names.to.plot<-top_n(Survey_', rank, '_Mean_Abund, 10, Survey_', rank, '_Mean)$', rank, '
}', sep = '')

  cat('\n# \n')
  
  cat('\nSurvey.',rank,'.A <- tax_glom(Survey, taxrank="',rank,'")\n',sep = '')
  
  cat('Survey.',rank,' <- prune_taxa(taxa_sums(Survey.',rank,'.A) > 0, Survey.',rank,'.A)\n',sep = '')

  cat('Survey.',rank,'.r  = transform_sample_counts(Survey.',rank,', function(x) x / sum(x) )\n',sep = '')

  cat('dat_Survey.',rank,'.r <- psmelt(Survey.',rank,'.r)\n',sep = '')

  cat('dat_Survey.',rank,'.r$',rank,' <- as.character(dat_Survey.',rank,'.r$',rank,') \n',sep = '')

  cat('dat_Survey.',rank,'.r$',rank,'_all <- dat_Survey.',rank,'.r$',rank,' \n',sep = '')
  
  cat('dat_Survey.',rank,'.r$',rank,' <- if_else(dat_Survey.',rank,'.r$',rank,' %in% Survey.',rank,'.names.to.plot, dat_Survey.',rank,'.r$',rank,', "LowAbundance") \n',sep = '')

  cat('\n## \n')

  cat('\n \n')

}

1.4.2 create vectors of top 10 taxa names

1.4.2.1 Survey

1.4.2.2 Exp

1.5 Group low abundance (!%inc% top 10 taxa)

(no generating code just copy paste)

1.5.1 Survey

2 Survey taxonomy

Phylum

Note: Bacterial and archaeal phyla with a global abundance of ≤ 0.58% relative abundance have been agglomerated into “≤ 0.58% relative abundance”. Vertical facets represent pits 1-4 and horizontal facets represent each basin-by-reach.

Class

Note: Bacterial and archaeal classes with a global abundance of ≤ 2.8% relative abundance have been agglomerated into “≤ 2.8% relative abundance”. Vertical facets represent pits 1-4 and horizontal facets represent each basin-by-reach.

Order

Note: Bacterial and archaeal orders with a global abundance of ≤ 3.7% relative abundance have been agglomerated into “≤ 3.7% relative abundance”. Vertical facets represent pits 1-4 and horizontal facets represent each basin-by-reach.

Family

Note: Bacterial and archaeal families with a global abundance of ≤ 3.7% relative abundance have been agglomerated into “≤ 3.7% relative abundance”. Vertical facets represent pits 1-4 and horizontal facets represent each basin-by-reach.