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CurrentModule = Microbiome
DocTestSetup  = quote
    using Microbiome
    using Microbiome.Dictionaries
end

Samples and Features

Microbial profiles are made up of AbstractSamples and AbstractFeatures. Typically, an AbstractSample is an individual biospecimen or other observation, and contains some number of AbstractFeatures, such as taxa or gene functions. AbstractSamples may also contain arbitrary metadata.

Sample types

At its most basic, an AbstractSample simply encodes a name (which should be a unique identifier), and a place to hold metadata. The concrete type MicrobiomeSample is implemented with these two fields, the latter of which is a Dictionary from Dictionaries.jl.

You can instantiate a MicrobiomeSample with just a name (in which case the metadata dictionary will be empty), using keyword arguments for metadata entries, or with existing metadata in the form of a dictionary (with keys of type Symbol) or a NamedTuple.

julia> s1 = MicrobiomeSample("sample1")
MicrobiomeSample("sample1", {})

julia> s2 = MicrobiomeSample("sample2"; age=37)
MicrobiomeSample("sample2", {:age = 37})

julia> s3 = MicrobiomeSample("sample3", Dict(:gender=>"female", :age=>23))
MicrobiomeSample("sample3", {:age = 23, :gender = "female"})

Working with metadata

To change or add metadata, you can use the same syntax as working with a [Dictionary] directly, though note that this is a bit different from the Dict type in base julia:

julia> insert!(s1, :age, 50)
MicrobiomeSample("sample1", {:age = 50})

julia> set!(s3, :gender, "nonbinary")
MicrobiomeSample("sample3", {:age = 23, :gender = "nonbinary"})

julia> delete!(s3, :gender)
MicrobiomeSample("sample3", {:age = 23})

You can access values of the dictionary using either getindex or getfield syntax, that is:

julia> s3[:age]
23

julia> s3.age
23

Bulk addiction of metadata is also possible, by passing a Dictionary or NamedTuple to set! or insert! (the latter will fail if any of the incoming keys are already found):

julia> insert!(s3, (gender = "nonbinary", genotype="XX"))
MicrobiomeSample("sample3", {:age = 23, :gender = "nonbinary", :genotype = "XX"})

julia> set!(s3, (genotype="XY", ses=7))
MicrobiomeSample("sample3", {:age = 23, :gender = "nonbinary", :genotype = "XY", :ses = 7})

Feature Types

AbstractFeature types also have a name, but other fields are optional. Microbiome.jl defines three concrete AbstractFeature types, Taxon, GeneFunction, and Metabolite.

Taxon

The Taxon type contains a name and (optionally) a rank (eg :phylum).

julia> ecoli = Taxon("Escherichia_coli", :species)
Taxon("Escherichia_coli", :species)

julia> uncl = Taxon("Unknown_bug")
Taxon("Unknown_bug", missing)

You can access the name and rank fields using name and taxrank respectively, and also check whether the instance has a rank with hasrank, which returns true or false.

julia> hasrank(ecoli)
true

julia> hasrank(uncl)
false

julia> taxrank(ecoli)
:species

julia> taxrank(uncl)
missing

julia> name(ecoli)
"Escherichia_coli"

julia> name(uncl)
"Unknown_bug"

For compatibility with other tools, converting a Taxon to a String will return the name prepended with the first letter of the taxonomic rank and 2 underscores. You can convert back using taxon (note the lowercase 't'):

julia> String(uncl)
"u__Unknown_bug"

julia> String(ecoli)
"s__Escherichia_coli"

julia> String(ecoli) |> Taxon
Taxon("s__Escherichia_coli", missing)

julia> String(ecoli) |> taxon
Taxon("Escherichia_coli", :species)

GeneFunction

The GeneFunction type contains a name and (optionally) a Taxon. In addition to providing both a name and Taxon, you can instantiate a GeneFunction with just a name (in which case the taxon will be missing), or with the name of the taxon (in which case it will not have a rank).

julia> gf1 = GeneFunction("gene1")
GeneFunction("gene1", missing)

julia> gf2 = GeneFunction("gene2", "Species_name")
GeneFunction("gene2", Taxon("Species_name", missing))

julia> gf3 = GeneFunction("gene2", Taxon("Species_name", :species))
GeneFunction("gene2", Taxon("Species_name", :species))

You can access or check for various fields using similar methods as for Taxon:

julia> hastaxon(gf1)
false

julia> hastaxon(gf2)
true

julia> hasrank(gf2)
false

julia> hasrank(gf3)
true

julia> name(gf3)
"gene2"

julia> taxon(gf3)
Taxon("Species_name", :species)

julia> taxrank(gf3)
:species

For compatibility with other tools, Converting a GeneFunction to a String if it has a Taxon will include the taxon name separated by |. Converting back can be done using genefunction (note the lowercase g and f).

julia> String(gf3)
"gene2|s__Species_name"

julia> genefunction(String(gf3))
GeneFunction("gene2", Taxon("Species_name", :species))

Metabolites

The Metabolite type has a name and optionally a commonname, a mass / charge ratio (mz), and retention time (rt).

julia> m = Metabolite("name", "common", 1., 2.)
Metabolite("name", "common", 1.0, 2.0)

julia> name(m)
"name"

julia> commonname(m)
"common"

julia> masscharge(m)
1.0

julia> retentiontime(m)
2.0

julia> m2 = Metabolite("other name")
Metabolite("other name", missing, missing, missing)

Types and Methods

MicrobiomeSample

Taxon
name
hasrank
taxrank
taxon

GeneFunction
genefunction

Metabolite
commonname
masscharge
retentiontime