Load OTU data.

The OTUs are treated the same as in the Variance Partitioning analysis, except that MD sites are removed before taxa are filtered by abundance.

otu= readRDS("~/Dropbox/sequence-processing-projects/21_sites/2020-01-01_set4/set4_vsearch-OTUs.RDS") %>% 
  subset_taxa( (Class!="Chloroplast" | is.na(Class) ) & !(is.na(Phylum)) & (Family!="mitochondria" | is.na(Family) ) ) %>%
  subset_samples(SamplingPeriod=="May_2018") %>%
  subset_samples(OilingLevel %in% c("HV","RF")) %>%
  filter_taxa(function(x) sum(x > 1) > 1, TRUE) %>%
  rarefy_even_depth(.)
tax_table(otu) = tax_table(otu)[,1:7]

# Transpose and transform
m18.sp = t(otu_table(otu))
# Hellinger: 
m18.sp = decostand(m18.sp, "hellinger")

md = data.frame(sample_data(otu))

Run indicator taxa analysis

I’m considering only the RF and HV sites. The R function is multipatt. The reference paper is: DeCaceres, M., Legendre, P., Moretti, M. 2010. Improving indicator species analysis by combining groups of sites. Oikos 119(10): 1674-1684.

may18ind = multipatt(m18.sp, md$OilingLevel, func = "IndVal.g", duleg=F, control = how(nperm=9999))
may18HV = data.frame(may18ind$sign) %>%
  filter(s.HV==1) %>%
  filter(p.value <= 0.05) 

may18RF = data.frame(may18ind$sign) %>%
  filter(s.RF==1)  %>%
  filter(p.value <= 0.05)

Significant indicators for HV sites

resHV = otu %>%
  transform_sample_counts(function(x) x / sum(x)) %>%
  subset_taxa(taxa_names(otu) %in% rownames(may18HV))

# calculate mean relative abundance (of HV and RF samples based on filtering above)
# resHV_RA = taxa_sums(resHV)/nsamples(resHV) 
# HV_tab = cbind(may18HV, Mean_RelAbund = round(resHV_RA, 3)) 

HV_tab = cbind(may18HV, data.frame(tax_table(resHV))) %>% select(-c(s.HV,s.RF,index)) %>% arrange(p.value) 

knitr::kable(HV_tab, row.names = F)
stat p.value Kingdom Phylum Class Order Family Genus Species
1.0000000 0.0007 Bacteria Deinococcus-Thermus Deinococci Thermales Thermaceae NA NA
1.0000000 0.0007 Bacteria Proteobacteria Alphaproteobacteria NA NA NA NA
1.0000000 0.0007 Bacteria Proteobacteria Alphaproteobacteria NA NA NA NA
1.0000000 0.0007 Bacteria Proteobacteria Gammaproteobacteria NA NA NA NA
1.0000000 0.0007 Bacteria Proteobacteria Gammaproteobacteria Acidithiobacillales Acidithiobacillaceae KCM-B-112 uncultured bacterium
1.0000000 0.0007 Bacteria Proteobacteria Gammaproteobacteria Immundisolibacterales Immundisolibacteraceae uncultured NA
1.0000000 0.0007 Bacteria Proteobacteria Gammaproteobacteria Oceanospirillales Pseudohongiellaceae Pseudohongiella NA
1.0000000 0.0007 Bacteria Proteobacteria Gammaproteobacteria Cellvibrionales Porticoccaceae C1-B045 NA
0.9366467 0.0017 Bacteria Proteobacteria Gammaproteobacteria Steroidobacterales Woeseiaceae Woeseia NA
0.9258201 0.0038 Bacteria Actinobacteria Actinobacteria Corynebacteriales Mycobacteriaceae Mycobacterium Ambiguous_taxa
0.9258201 0.0038 Bacteria Proteobacteria NA NA NA NA NA
0.9258201 0.0038 Bacteria Proteobacteria Deltaproteobacteria Desulfovibrionales Desulfovibrionaceae Desulfovibrio Ambiguous_taxa
0.9258201 0.0041 Bacteria Proteobacteria Gammaproteobacteria Ectothiorhodospirales Thioalkalispiraceae Thiohalophilus NA
0.9258201 0.0042 Bacteria Deferribacteres Deferribacteres Deferribacterales Deferribacteraceae uncultured uncultured Deferribacteres bacterium
0.9258201 0.0042 Bacteria Proteobacteria Gammaproteobacteria Ectothiorhodospirales Ectothiorhodospiraceae Thiogranum NA
0.8687282 0.0078 Bacteria Bacteroidetes Bacteroidia Chitinophagales Saprospiraceae uncultured NA
0.8725543 0.0117 Bacteria Proteobacteria Deltaproteobacteria Desulfobacterales Desulfobacteraceae SEEP-SRB1 uncultured bacterium
0.8491389 0.0182 Bacteria Acidobacteria Subgroup 21 uncultured bacterium uncultured bacterium uncultured bacterium uncultured bacterium
0.8451543 0.0184 Bacteria Proteobacteria Gammaproteobacteria Cellvibrionales Porticoccaceae C1-B045 uncultured gamma proteobacterium
0.8066309 0.0198 Bacteria Bacteroidetes Bacteroidia Sphingobacteriales NA NA NA
0.8451543 0.0198 Bacteria Proteobacteria Gammaproteobacteria Oceanospirillales Alcanivoracaceae Alcanivorax NA
0.8451543 0.0202 Bacteria Epsilonbacteraeota Campylobacteria Campylobacterales Thiovulaceae Sulfurimonas NA
0.8451543 0.0202 Bacteria Bacteroidetes Bacteroidia Bacteroidales Prolixibacteraceae NA NA
0.8199735 0.0202 Bacteria Planctomycetes Pla4 lineage NA NA NA NA
0.8451543 0.0202 Bacteria Proteobacteria Deltaproteobacteria Desulfarculales Desulfarculaceae NA NA
0.8451543 0.0202 Bacteria Proteobacteria Gammaproteobacteria Betaproteobacteriales Gallionellaceae Candidatus Nitrotoga NA
0.8142142 0.0202 Bacteria Proteobacteria Gammaproteobacteria Chromatiales NA NA NA
0.8451543 0.0202 Bacteria Proteobacteria Gammaproteobacteria Immundisolibacterales Immundisolibacteraceae NA NA
0.8451543 0.0211 Bacteria Bacteroidetes Bacteroidia Cytophagales Cyclobacteriaceae uncultured NA
0.8451543 0.0228 Bacteria Chloroflexi Anaerolineae Anaerolineales Anaerolineaceae uncultured uncultured bacterium
0.7821963 0.0348 Bacteria Spirochaetes Spirochaetia Spirochaetales Spirochaetaceae Spirochaeta 2 NA
0.8210749 0.0364 Bacteria Proteobacteria Gammaproteobacteria NA NA NA NA
0.7859200 0.0377 Bacteria Proteobacteria Alphaproteobacteria NA NA NA NA
0.7872623 0.0431 Bacteria Planctomycetes Phycisphaerae NA NA NA NA
0.7604379 0.0437 Bacteria Proteobacteria Gammaproteobacteria Alteromonadales NA NA NA

Significant indicators for RF sites (showing 20/168)

resRF = otu %>%
  transform_sample_counts(function(x) x / sum(x)) %>%
  subset_taxa(taxa_names(otu) %in% rownames(may18RF)) 

RF_tab = cbind(may18RF, data.frame(tax_table(resRF))) %>% select(-c(s.HV,s.RF,index)) %>% arrange(p.value)

knitr::kable(RF_tab[1:20,], row.names = F)
stat p.value Kingdom Phylum Class Order Family Genus Species
1.0000000 0.0007 Bacteria Proteobacteria Alphaproteobacteria Acetobacterales Acetobacteraceae NA NA
0.9544651 0.0007 Bacteria Proteobacteria Alphaproteobacteria Reyranellales Reyranellaceae Reyranella NA
1.0000000 0.0007 Bacteria Chloroflexi Anaerolineae RBG-13-54-9 uncultured bacterium uncultured bacterium uncultured bacterium
1.0000000 0.0007 Bacteria Verrucomicrobia Verrucomicrobiae Pedosphaerales Pedosphaeraceae uncultured bacterium uncultured bacterium
1.0000000 0.0007 Bacteria Proteobacteria Deltaproteobacteria Desulfuromonadales Sva1033 NA NA
1.0000000 0.0007 Bacteria Proteobacteria Gammaproteobacteria KI89A clade NA NA NA
1.0000000 0.0007 Bacteria Proteobacteria Gammaproteobacteria Alteromonadales Colwelliaceae Thalassotalea NA
0.9577520 0.0009 Bacteria Cyanobacteria Oxyphotobacteria Chloroplast NA NA NA
0.9118706 0.0016 Bacteria Nitrospirae Nitrospira Nitrospirales Nitrospiraceae Nitrospira uncultured bacterium
0.8682361 0.0018 Bacteria Chloroflexi Anaerolineae SBR1031 A4b NA NA
0.9446638 0.0018 Bacteria Proteobacteria Deltaproteobacteria Myxococcales Sandaracinaceae uncultured NA
0.9481443 0.0020 Bacteria Acidobacteria NA NA NA NA NA
0.9384220 0.0021 Bacteria Chloroflexi KD4-96 uncultured bacterium uncultured bacterium uncultured bacterium uncultured bacterium
0.9346049 0.0021 Bacteria Proteobacteria Gammaproteobacteria Acidiferrobacterales Acidiferrobacteraceae Sulfurifustis NA
0.9235892 0.0022 Bacteria Proteobacteria Deltaproteobacteria Desulfobacterales Desulfobulbaceae NA NA
0.8837933 0.0031 Bacteria Bacteroidetes Bacteroidia Chitinophagales Saprospiraceae uncultured NA
0.9202534 0.0031 Bacteria Kiritimatiellaeota Kiritimatiellae Kiritimatiellales Kiritimatiellaceae R76-B128 NA
0.9266534 0.0032 Bacteria Proteobacteria Gammaproteobacteria Betaproteobacteriales NA NA NA
0.9068840 0.0033 Bacteria Proteobacteria Gammaproteobacteria NA NA NA NA
0.9258201 0.0034 Bacteria Bacteroidetes Bacteroidia Chitinophagales Saprospiraceae uncultured NA

Get the relative abundance of the top indicators?