Metagenomics
2023-02-01
First we are going to load our required library for this analysis, which is SQMtools
Since we ran this analysis in sequential mode (one sample at a time), we have output files for each sample run. We now need to combine these samples into a single file using the ‘coimbineSQMlite’ command
We’ll first combine the first 4 sample datasets (which represent a single biological sample)
We’ll now combine the next 4 datasets into the second biological sample for AT340Sed
And finaly the last four datasets into the last biological sample.
ATS Deep Seep
These are the taxa identified for the ATS Deep Seep samples
Kingdom
All_ATS <- combineSQMlite(ATS_Sample_1, ATS_Sample_2, ATS_Sample_3)
plotTaxonomy(All_ATS, rank='superkingdom', count='percent', ignore_unmapped = TRUE)## Warning in mostAbundant(data, N = N, items = tax, others = others, rescale =
## rescale): N=15 but only 7 items exist. Returning 7 items## Warning in mostAbundant(data, N = N + rr, items = tax, others = others, : N=16
## but only 7 items exist. Returning 7 items
Phylum
All_ATS <- combineSQMlite(ATS_Sample_1, ATS_Sample_2, ATS_Sample_3)
plotTaxonomy(All_ATS, rank='phylum', count='percent', ignore_unmapped = TRUE)
Class
All_ATS <- combineSQMlite(ATS_Sample_1, ATS_Sample_2, ATS_Sample_3)
plotTaxonomy(All_ATS, rank='class', count='percent', ignore_unmapped = TRUE)
Order
All_ATS <- combineSQMlite(ATS_Sample_1, ATS_Sample_2, ATS_Sample_3)
plotTaxonomy(All_ATS, rank='order', count='percent', ignore_unmapped = TRUE)
Family
All_ATS <- combineSQMlite(ATS_Sample_1, ATS_Sample_2, ATS_Sample_3)
plotTaxonomy(All_ATS, rank='family', count='percent', ignore_unmapped = TRUE)
Species
All_ATS <- combineSQMlite(ATS_Sample_1, ATS_Sample_2, ATS_Sample_3)
plotTaxonomy(All_ATS, rank='species', count='percent', ignore_unmapped = TRUE)
Avery Island Sediment
These are the taxa identified for the Avery Island samples
Kingdom
All_Sed <- combineSQMlite(Sed_Sample_1, Sed_Sample_2, Sed_Sample_3)
plotTaxonomy(All_Sed, rank='superkingdom', count='percent', ignore_unmapped = TRUE)## Warning in mostAbundant(data, N = N, items = tax, others = others, rescale =
## rescale): N=15 but only 7 items exist. Returning 7 items## Warning in mostAbundant(data, N = N + rr, items = tax, others = others, : N=16
## but only 7 items exist. Returning 7 items
Phylum
All_Sed <- combineSQMlite(Sed_Sample_1, Sed_Sample_2, Sed_Sample_3)
plotTaxonomy(All_Sed, rank='phylum', count='percent', ignore_unmapped = TRUE)
Genus
All_Sed <- combineSQMlite(Sed_Sample_1, Sed_Sample_2, Sed_Sample_3)
plotTaxonomy(All_Sed, rank='genus', count='percent', ignore_unmapped = TRUE)
Order
All_Sed <- combineSQMlite(Sed_Sample_1, Sed_Sample_2, Sed_Sample_3)
plotTaxonomy(All_Sed, rank='order', count='percent', ignore_unmapped = TRUE)
Family
All_Sed <- combineSQMlite(Sed_Sample_1, Sed_Sample_2, Sed_Sample_3)
plotTaxonomy(All_Sed, rank='family', count='percent', ignore_unmapped = TRUE)
Species
All_Sed <- combineSQMlite(Sed_Sample_1, Sed_Sample_2, Sed_Sample_3)
plotTaxonomy(All_Sed, rank='species', count='percent', ignore_unmapped = TRUE)
Spores Protocol
These are the taxa identified for the Spore protocol samples
Kingdom
All_Spore <- combineSQMlite(Spore_Sample_1, Spore_Sample_2, Spore_Sample_3)
plotTaxonomy(All_Spore, rank='superkingdom', count='percent', ignore_unmapped = TRUE)## Warning in mostAbundant(data, N = N, items = tax, others = others, rescale =
## rescale): N=15 but only 7 items exist. Returning 7 items## Warning in mostAbundant(data, N = N + rr, items = tax, others = others, : N=16
## but only 7 items exist. Returning 7 items
Phylum
All_Spore <- combineSQMlite(Spore_Sample_1, Spore_Sample_2, Spore_Sample_3)
plotTaxonomy(All_Spore, rank='phylum', count='percent', ignore_unmapped = TRUE)
Genus
All_Spore <- combineSQMlite(Spore_Sample_1, Spore_Sample_2, Spore_Sample_3)
plotTaxonomy(All_Spore, rank='genus', count='percent', ignore_unmapped = TRUE)
Order
All_Spore <- combineSQMlite(Spore_Sample_1, Spore_Sample_2, Spore_Sample_3)
plotTaxonomy(All_Spore, rank='order', count='percent', ignore_unmapped = TRUE)
Family
All_Spore <- combineSQMlite(Spore_Sample_1, Spore_Sample_2, Spore_Sample_3)
plotTaxonomy(All_Spore, rank='family', count='percent', ignore_unmapped = TRUE)
Species
All_Spore <- combineSQMlite(Spore_Sample_1, Spore_Sample_2, Spore_Sample_3)
plotTaxonomy(All_Spore, rank='species', count='percent', ignore_unmapped = TRUE)
Pathway Analysis
ATS Deep Seep
These are the pathways identified
Kegg Pathways
plotFunctions(All_ATS, fun_level = 'KEGG', count = 'copy_number', N = 8, base_size = 28)
COG Pathways
plotFunctions(All_ATS, fun_level = 'COG', count = 'copy_number', N = 8, base_size = 28)
PFAM Pathways
plotFunctions(All_ATS, fun_level = 'PFAM', count = 'copy_number', N = 8, base_size = 28)
Avery Island Sediment
Kegg Pathways
plotFunctions(All_Sed, fun_level = 'KEGG', count = 'copy_number', N = 8, base_size = 28)
Sediment COG Pathways
plotFunctions(All_Sed, fun_level = 'COG', count = 'copy_number', N = 8, base_size = 28)
PFAM Pathways
plotFunctions(All_Sed, fun_level = 'PFAM', count = 'copy_number', N = 8, base_size = 28)
Spore Protocol
Spore Kegg Pathways
plotFunctions(All_Spore, fun_level = 'PFAM', count = 'tpm', N = 8 , base_size = 28)
COG Pathways
plotFunctions(All_Spore, fun_level = 'COG', count = 'tpm', N = 8, base_size = 28 )
PFAM Pathways
plotFunctions(All_Spore, fun_level = 'COG', count = 'tpm', N = 8, base_size = 28 )
Pathways of interest
Antibiotics
ATS Deep Seep
antibiotic1 = subsetFun(ATS1, fun = 'antibiotic', rescale_copy_number = F)
antibiotic2 = subsetFun(ATS2, fun = 'antibiotic', rescale_copy_number = F)
antibiotic3 = subsetFun(ATS3, fun = 'antibiotic', rescale_copy_number = F)
antibiotic4 = subsetFun(ATS4, fun = 'antibiotic', rescale_copy_number = F)
antibiotic5 = subsetFun(ATS5, fun = 'antibiotic', rescale_copy_number = F)
antibiotic6 = subsetFun(ATS6, fun = 'antibiotic', rescale_copy_number = F)
antibiotic7 = subsetFun(ATS7, fun = 'antibiotic', rescale_copy_number = F)
antibiotic8 = subsetFun(ATS8, fun = 'antibiotic', rescale_copy_number = F)
antibiotic9 = subsetFun(ATS9, fun = 'antibiotic', rescale_copy_number = F)
antibiotic10 = subsetFun(ATS10, fun = 'antibiotic', rescale_copy_number = F)
antibiotic11 = subsetFun(ATS11, fun = 'antibiotic', rescale_copy_number = F)
antibiotic12 = subsetFun(ATS12, fun = 'antibiotic', rescale_copy_number = F)
ATS_Antibiotics <- combineSQMlite(antibiotic1, antibiotic2, antibiotic3, antibiotic4, antibiotic5, antibiotic6, antibiotic7, antibiotic8, antibiotic9, antibiotic10, antibiotic11, antibiotic12)
plotTaxonomy(ATS_Antibiotics, rank = 'genus', count = 'percent', base_size = 20)
Avery Island Sediment
antibiotic1 = subsetFun(Sed1, fun = 'antibiotic', rescale_copy_number = F)
antibiotic2 = subsetFun(Sed2, fun = 'antibiotic', rescale_copy_number = F)
antibiotic3 = subsetFun(Sed3, fun = 'antibiotic', rescale_copy_number = F)
antibiotic4 = subsetFun(Sed4, fun = 'antibiotic', rescale_copy_number = F)
antibiotic5 = subsetFun(Sed5, fun = 'antibiotic', rescale_copy_number = F)
antibiotic6 = subsetFun(Sed6, fun = 'antibiotic', rescale_copy_number = F)
antibiotic7 = subsetFun(Sed7, fun = 'antibiotic', rescale_copy_number = F)
antibiotic8 = subsetFun(Sed8, fun = 'antibiotic', rescale_copy_number = F)
antibiotic9 = subsetFun(Sed9, fun = 'antibiotic', rescale_copy_number = F)
antibiotic10 = subsetFun(Sed10, fun = 'antibiotic', rescale_copy_number = F)
antibiotic11 = subsetFun(Sed11, fun = 'antibiotic', rescale_copy_number = F)
antibiotic12 = subsetFun(Sed12, fun = 'antibiotic', rescale_copy_number = F)
Sed_Antibiotics <- combineSQMlite(antibiotic1, antibiotic2, antibiotic3, antibiotic4, antibiotic5, antibiotic6, antibiotic7, antibiotic8, antibiotic9, antibiotic10, antibiotic11, antibiotic12)
plotTaxonomy(Sed_Antibiotics, rank = 'genus', count = 'percent', base_size = 20)
Spore Protocol
antibiotic1 = subsetFun(Spore1, fun = 'antibiotic', rescale_copy_number = F)
antibiotic2 = subsetFun(Spore2, fun = 'antibiotic', rescale_copy_number = F)
antibiotic3 = subsetFun(Spore3, fun = 'antibiotic', rescale_copy_number = F)
antibiotic4 = subsetFun(Spore4, fun = 'antibiotic', rescale_copy_number = F)
antibiotic5 = subsetFun(Spore5, fun = 'antibiotic', rescale_copy_number = F)
antibiotic6 = subsetFun(Spore6, fun = 'antibiotic', rescale_copy_number = F)
antibiotic7 = subsetFun(Spore7, fun = 'antibiotic', rescale_copy_number = F)
antibiotic8 = subsetFun(Spore8, fun = 'antibiotic', rescale_copy_number = F)
antibiotic9 = subsetFun(Spore9, fun = 'antibiotic', rescale_copy_number = F)
antibiotic10 = subsetFun(Spore10, fun = 'antibiotic', rescale_copy_number = F)
antibiotic11 = subsetFun(Spore11, fun = 'antibiotic', rescale_copy_number = F)
antibiotic12 = subsetFun(Spore12, fun = 'antibiotic', rescale_copy_number = F)
Spore_Antibiotics <- combineSQMlite(antibiotic1, antibiotic2, antibiotic3, antibiotic4, antibiotic5, antibiotic6, antibiotic7, antibiotic8, antibiotic9, antibiotic10, antibiotic11, antibiotic12)
plotTaxonomy(Spore_Antibiotics, rank = 'genus', count = 'percent', base_size = 20)