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joey711 / phyloseq

phyloseq is a set of classes, wrappers, and tools (in R) to make it easier to import, store, and analyze phylogenetic sequencing data; and to reproducibly share that data and analysis with others. See the phyloseq front page:
http://joey711.github.io/phyloseq/
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Understanding plot_heatmap results #1470

Open ValPoltr opened 3 years ago

ValPoltr commented 3 years ago

Screenshot from 2021-05-26 14-32-21 Hello dear colleagues! I'm a student. And i just started learning these methods. Could someone help me understand some of the details on this plot:

  1. Why species are repeated on axis y?
  2. What do the gaps between species on the same axis mean? It's a metagenome of fungi on grapes. Thanks for any help!

top100ITSsklearn <- names(sort(taxa_sums(ITSsklearn), decreasing=TRUE))[1:20]

ITSsklearn.top20 <- transform_sample_counts(ITSsklearn, function(OTU) OTU / sum(OTU))

ITSsklearn.top20 <- prune_taxa(top20ITSsklearn, ITSsklearn.top20)

plot_heatmap(ITSsklearn.top20, method = "MDS", taxa.label = "Species", trans = NULL, low = "beige", high = "red", na.value = "beige", distance = 'bray')+ theme (axis.text.y = element_text(size=16))

ycl6 commented 3 years ago

Hi @ValPoltr, the reason for the repeating Species names in the plot is because that was what's been annotated in the tax_table. As to the second question, I think those gaps indicate the Species fields of those taxa in the tax_table are NA.

Below I use the test dataset GlobalPatterns to show what is happening:

library(phyloseq)
data(GlobalPatterns)

top_taxa <- names(sort(taxa_sums(GlobalPatterns), decreasing = TRUE))[1:20]
top_gp <- transform_sample_counts(GlobalPatterns, function(OTU) OTU / sum(OTU))
top_gp <- prune_taxa(top_taxa, top_gp)

# show Taxonomy Table
tax_table(top_gp)
Taxonomy Table:     [20 taxa by 7 taxonomic ranks]:
       Kingdom    Phylum           Class                 Order               Family               Genus              Species                      
12812  "Bacteria" "Actinobacteria" "Actinobacteria"      "koll13"            NA                   NA                 NA                           
317658 "Bacteria" "Actinobacteria" "Actinobacteria"      "Actinomycetales"   "ACK-M1"             NA                 NA                           
329744 "Bacteria" "Actinobacteria" "Actinobacteria"      "Actinomycetales"   "ACK-M1"             NA                 NA                           
326977 "Bacteria" "Actinobacteria" "Actinobacteria"      "Bifidobacteriales" "Bifidobacteriaceae" "Bifidobacterium"  "Bifidobacteriumadolescentis"
317182 "Bacteria" "Cyanobacteria"  "Chloroplast"         "Stramenopiles"     NA                   NA                 NA                           
549656 "Bacteria" "Cyanobacteria"  "Chloroplast"         "Stramenopiles"     NA                   NA                 NA                           
279599 "Bacteria" "Cyanobacteria"  "Nostocophycideae"    "Nostocales"        "Nostocaceae"        "Dolichospermum"   NA                           
263681 "Bacteria" "Cyanobacteria"  "4C0d-2"              "YS2"               NA                   NA                 NA                           
360229 "Bacteria" "Proteobacteria" "Betaproteobacteria"  "Neisseriales"      "Neisseriaceae"      "Neisseria"        NA                           
536311 "Bacteria" "Proteobacteria" "Betaproteobacteria"  "Neisseriales"      "Neisseriaceae"      "Kingella"         NA                           
94166  "Bacteria" "Proteobacteria" "Gammaproteobacteria" "Pasteurellales"    "Pasteurellaceae"    "Haemophilus"      "Haemophilusparainfluenzae"  
550960 "Bacteria" "Proteobacteria" "Gammaproteobacteria" "Enterobacteriales" "Enterobacteriaceae" "Providencia"      NA                           
158660 "Bacteria" "Bacteroidetes"  "Bacteroidia"         "Bacteroidales"     "Bacteroidaceae"     "Bacteroides"      NA                           
331820 "Bacteria" "Bacteroidetes"  "Bacteroidia"         "Bacteroidales"     "Bacteroidaceae"     "Bacteroides"      NA                           
244304 "Bacteria" "Bacteroidetes"  "Bacteroidia"         "Bacteroidales"     "Bacteroidaceae"     "Bacteroides"      NA                           
298875 "Bacteria" "Firmicutes"     "Clostridia"          "Clostridiales"     "Clostridiaceae"     "Clostridium"      NA                           
192573 "Bacteria" "Firmicutes"     "Clostridia"          "Clostridiales"     "Ruminococcaceae"    NA                 NA                           
171551 "Bacteria" "Firmicutes"     "Clostridia"          "Clostridiales"     "Ruminococcaceae"    "Faecalibacterium" "Faecalibacteriumprausnitzii"
189047 "Bacteria" "Firmicutes"     "Clostridia"          "Clostridiales"     "Ruminococcaceae"    NA                 NA                           
98605  "Bacteria" "Firmicutes"     "Bacilli"             "Lactobacillales"   "Streptococcaceae"   "Streptococcus"    "Streptococcussanguinis"

default taxa.label = NULL (show taxa_names)

plot_heatmap(top_gp, method = "MDS", taxa.label = NULL, trans = NULL, low = "beige", high = "red", na.value = "beige", distance = "bray")

taxa.label = NULL

taxa.label = "Genus"

plot_heatmap(top_gp, method = "MDS", taxa.label = "Genus", trans = NULL, low = "beige", high = "red", na.value = "beige", distance = "bray")

taxa.label = "Genus"

taxa.label = "Species"

plot_heatmap(top_gp, method = "MDS", taxa.label = "Species", trans = NULL, low = "beige", high = "red", na.value = "beige", distance = "bray")

taxa.label = "Species"

mafbio commented 3 years ago

Hello,

I understood your comment @ycl6, but it is the possibility to join the different taxonomic levels respectively, in order to avoid the repetition in the y axis?

Many thanks

ycl6 commented 3 years ago

Yes @mafbio, you can use tax_glom to agglomerate taxa (see below). The abundance will be added up in the agglomerated object and you can use it to plot heatmap.

As you can see from the resulting tax table, ASVs that have no taxonomy assignment with the specified rank (e.g. Genus) get removed. So if this is not what you want, you need to modified your tax table so that instead of NA you give those a string description, e.g. unassigned, unknown, etc.

library(phyloseq)
data(GlobalPatterns)

top_taxa <- names(sort(taxa_sums(GlobalPatterns), decreasing = TRUE))[1:20]
top_gp <- transform_sample_counts(GlobalPatterns, function(OTU) OTU / sum(OTU))
top_gp <- prune_taxa(top_taxa, top_gp)
> top_gp
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 20 taxa and 26 samples ]
sample_data() Sample Data:       [ 26 samples by 7 sample variables ]
tax_table()   Taxonomy Table:    [ 20 taxa by 7 taxonomic ranks ]
phy_tree()    Phylogenetic Tree: [ 20 tips and 19 internal nodes ]

> tax_table(top_gp)
Taxonomy Table:     [20 taxa by 7 taxonomic ranks]:
       Kingdom    Phylum           Class                 Order               Family               Genus              Species                      
12812  "Bacteria" "Actinobacteria" "Actinobacteria"      "koll13"            NA                   NA                 NA                           
317658 "Bacteria" "Actinobacteria" "Actinobacteria"      "Actinomycetales"   "ACK-M1"             NA                 NA                           
329744 "Bacteria" "Actinobacteria" "Actinobacteria"      "Actinomycetales"   "ACK-M1"             NA                 NA                           
326977 "Bacteria" "Actinobacteria" "Actinobacteria"      "Bifidobacteriales" "Bifidobacteriaceae" "Bifidobacterium"  "Bifidobacteriumadolescentis"
317182 "Bacteria" "Cyanobacteria"  "Chloroplast"         "Stramenopiles"     NA                   NA                 NA                           
549656 "Bacteria" "Cyanobacteria"  "Chloroplast"         "Stramenopiles"     NA                   NA                 NA                           
279599 "Bacteria" "Cyanobacteria"  "Nostocophycideae"    "Nostocales"        "Nostocaceae"        "Dolichospermum"   NA                           
263681 "Bacteria" "Cyanobacteria"  "4C0d-2"              "YS2"               NA                   NA                 NA                           
360229 "Bacteria" "Proteobacteria" "Betaproteobacteria"  "Neisseriales"      "Neisseriaceae"      "Neisseria"        NA                           
536311 "Bacteria" "Proteobacteria" "Betaproteobacteria"  "Neisseriales"      "Neisseriaceae"      "Kingella"         NA                           
94166  "Bacteria" "Proteobacteria" "Gammaproteobacteria" "Pasteurellales"    "Pasteurellaceae"    "Haemophilus"      "Haemophilusparainfluenzae"  
550960 "Bacteria" "Proteobacteria" "Gammaproteobacteria" "Enterobacteriales" "Enterobacteriaceae" "Providencia"      NA                           
158660 "Bacteria" "Bacteroidetes"  "Bacteroidia"         "Bacteroidales"     "Bacteroidaceae"     "Bacteroides"      NA                           
331820 "Bacteria" "Bacteroidetes"  "Bacteroidia"         "Bacteroidales"     "Bacteroidaceae"     "Bacteroides"      NA                           
244304 "Bacteria" "Bacteroidetes"  "Bacteroidia"         "Bacteroidales"     "Bacteroidaceae"     "Bacteroides"      NA                           
298875 "Bacteria" "Firmicutes"     "Clostridia"          "Clostridiales"     "Clostridiaceae"     "Clostridium"      NA                           
192573 "Bacteria" "Firmicutes"     "Clostridia"          "Clostridiales"     "Ruminococcaceae"    NA                 NA                           
171551 "Bacteria" "Firmicutes"     "Clostridia"          "Clostridiales"     "Ruminococcaceae"    "Faecalibacterium" "Faecalibacteriumprausnitzii"
189047 "Bacteria" "Firmicutes"     "Clostridia"          "Clostridiales"     "Ruminococcaceae"    NA                 NA                           
98605  "Bacteria" "Firmicutes"     "Bacilli"             "Lactobacillales"   "Streptococcaceae"   "Streptococcus"    "Streptococcussanguinis"     
top_gp_g <- tax_glom(top_gp, taxrank = "Genus")
> top_gp_g 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 10 taxa and 26 samples ]
sample_data() Sample Data:       [ 26 samples by 7 sample variables ]
tax_table()   Taxonomy Table:    [ 10 taxa by 7 taxonomic ranks ]
phy_tree()    Phylogenetic Tree: [ 10 tips and 9 internal nodes ]

> tax_table(top_gp_g)
Taxonomy Table:     [10 taxa by 7 taxonomic ranks]:
       Kingdom    Phylum           Class                 Order               Family               Genus              Species
326977 "Bacteria" "Actinobacteria" "Actinobacteria"      "Bifidobacteriales" "Bifidobacteriaceae" "Bifidobacterium"  NA     
279599 "Bacteria" "Cyanobacteria"  "Nostocophycideae"    "Nostocales"        "Nostocaceae"        "Dolichospermum"   NA     
360229 "Bacteria" "Proteobacteria" "Betaproteobacteria"  "Neisseriales"      "Neisseriaceae"      "Neisseria"        NA     
536311 "Bacteria" "Proteobacteria" "Betaproteobacteria"  "Neisseriales"      "Neisseriaceae"      "Kingella"         NA     
94166  "Bacteria" "Proteobacteria" "Gammaproteobacteria" "Pasteurellales"    "Pasteurellaceae"    "Haemophilus"      NA     
550960 "Bacteria" "Proteobacteria" "Gammaproteobacteria" "Enterobacteriales" "Enterobacteriaceae" "Providencia"      NA     
331820 "Bacteria" "Bacteroidetes"  "Bacteroidia"         "Bacteroidales"     "Bacteroidaceae"     "Bacteroides"      NA     
298875 "Bacteria" "Firmicutes"     "Clostridia"          "Clostridiales"     "Clostridiaceae"     "Clostridium"      NA     
171551 "Bacteria" "Firmicutes"     "Clostridia"          "Clostridiales"     "Ruminococcaceae"    "Faecalibacterium" NA     
98605  "Bacteria" "Firmicutes"     "Bacilli"             "Lactobacillales"   "Streptococcaceae"   "Streptococcus"    NA
mafbio commented 3 years ago

Thank you very much for the information. It has been a great help