taxa

Build Status codecov Project Status: WIP - Initial development is in progress, but there has not yet been a stable, usable release suitable for the public. rstudio mirror downloads cran version

taxa defines taxonomic classes and functions to manipulate them. The goal is to use these classes as low level fundamental taxonomic classes that other R packages can build on and use.

There are two distinct types of classes in taxa:

Diagram of class concepts for taxa classes:

Install

CRAN version

install.packages("taxa")

Development version from GitHub

devtools::install_github("ropensci/taxa")

library("taxa")

The classes

Minor component classes

There are a few optional classes used to store information in other classes. In most cases, these can be replaced with simple character values but using them provides more information and potential functionality.

database

Taxonomic data usually comes from a database. A common example is the NCBI Taxonomy Database used to provide taxonomic classifications to sequences deposited in other NCBI databases. The database class stores the name of the database and associated information:

(ncbi <- taxon_database(
  name = "ncbi",
  url = "http://www.ncbi.nlm.nih.gov/taxonomy",
  description = "NCBI Taxonomy Database",
  id_regex = "*"
))
#> <database> ncbi
#>   url: http://www.ncbi.nlm.nih.gov/taxonomy
#>   description: NCBI Taxonomy Database
#>   id regex: *
ncbi$name
#> [1] "ncbi"
ncbi$url
#> [1] "http://www.ncbi.nlm.nih.gov/taxonomy"

To save on memory, a selection of common databases is provided with the package (database_list) and any in this list can be used by name instead of making a new database object (e.g. "ncbi" instead of the ncbi above).

database_list
#> $ncbi
#> <database> ncbi
#>   url: http://www.ncbi.nlm.nih.gov/taxonomy
#>   description: NCBI Taxonomy Database
#>   id regex: .*
#> 
#> $gbif
#> <database> gbif
#>   url: http://www.gbif.org/developer/species
#>   description: GBIF Taxonomic Backbone
#>   id regex: .*
#> 
#> $bold
#> <database> bold
#>   url: http://www.boldsystems.org
#>   description: Barcode of Life
#>   id regex: .*
#> 
#> $col
#> <database> col
#>   url: http://www.catalogueoflife.org
#>   description: Catalogue of Life
#>   id regex: .*
#> 
#> $eol
#> <database> eol
#>   url: http://eol.org
#>   description: Encyclopedia of Life
#>   id regex: .*
#> 
#> $nbn
#> <database> nbn
#>   url: https://nbn.org.uk
#>   description: UK National Biodiversity Network
#>   id regex: .*
#> 
#> $tps
#> <database> tps
#>   url: http://www.tropicos.org/
#>   description: Tropicos
#>   id regex: .*
#> 
#> $itis
#> <database> itis
#>   url: http://www.itis.gov
#>   description: Integrated Taxonomic Information System
#>   id regex: .*

rank

Taxa might have defined ranks (e.g. species, family, etc.), ambiguous ranks (e.g. “unranked”, “unknown”), or no rank information at all. The particular selection and format of valid ranks varies with database, so the database can be optionally defined. If no database is defined, any ranks in any order are allowed.

taxon_rank(name = "species", database = "ncbi")
#> <TaxonRank> species
#>   database: ncbi

taxon_name

The taxon name can be defined in the same way as rank.

taxon_name("Poa", database = "ncbi")
#> <TaxonName> Poa
#>   database: ncbi

taxon_id

Each database has its set of unique taxon IDs. These IDs are better than using the taxon name directly because they are guaranteed to be unique, whereas there are often duplicates of taxon names (e.g. Orestias elegans is the name of both an orchid and a fish).

taxon_id(12345, database = "ncbi")
#> <TaxonId> 12345
#>   database: ncbi

The “taxon” class

The taxon class combines the classes containing the name, rank, and ID for the taxon. There is also a place to define an authority of the taxon.

(x <- taxon(
  name = taxon_name("Poa annua"),
  rank = taxon_rank("species"),
  id = taxon_id(93036),
  authority = "Linnaeus"
))
#> <Taxon>
#>   name: Poa annua
#>   rank: species
#>   id: 93036
#>   authority: none

Instead of the name, rank, and ID classes, simple character vectors can be supplied.

(x <- taxon(
  name = "Poa annua",
  rank = "species",
  id = 93036,
  authority = "Linnaeus"
))
#> <Taxon>
#>   name: Poa annua
#>   rank: species
#>   id: 93036
#>   authority: none

The taxa class is just a list of taxon classes with some custom print methods. It is meant to store an arbitrary list of taxon.

(x <- taxon(
  name = taxon_name("Poa annua"),
  rank = taxon_rank("species"),
  id = taxon_id(93036)
))
#> <Taxon>
#>   name: Poa annua
#>   rank: species
#>   id: 93036
#>   authority: none
taxa(x, x, x)
#> <taxa> 
#>   no. taxa:  3 
#>   Poa annua / species / 93036 
#>   Poa annua / species / 93036 
#>   Poa annua / species / 93036

The “hierarchy” class

Taxonomic classifications are an ordered set of taxa, each at a different rank. The hierarchy class stores a list of taxon classes like taxa, but hierarchy is meant to store all of the taxa in a classification in the correct order.

x <- taxon(
  name = taxon_name("Poaceae"),
  rank = taxon_rank("family"),
  id = taxon_id(4479)
)

y <- taxon(
  name = taxon_name("Poa"),
  rank = taxon_rank("genus"),
  id = taxon_id(4544)
)

z <- taxon(
  name = taxon_name("Poa annua"),
  rank = taxon_rank("species"),
  id = taxon_id(93036)
)

(hier1 <- hierarchy(z, y, x))
#> <Hierarchy>
#>   no. taxon's:  3 
#>   Poaceae / family / 4479 
#>   Poa / genus / 4544 
#>   Poa annua / species / 93036

Multiple hierarchy classes are stored in the hierarchies class, similar to how multiple taxon are stored in taxa.

a <- taxon(
  name = taxon_name("Felidae"),
  rank = taxon_rank("family"),
  id = taxon_id(9681)
)
b <- taxon(
  name = taxon_name("Puma"),
  rank = taxon_rank("genus"),
  id = taxon_id(146712)
)
c <- taxon(
  name = taxon_name("Puma concolor"),
  rank = taxon_rank("species"),
  id = taxon_id(9696)
)
(hier2 <- hierarchy(c, b, a))
#> <Hierarchy>
#>   no. taxon's:  3 
#>   Felidae / family / 9681 
#>   Puma / genus / 146712 
#>   Puma concolor / species / 9696

hierarchies(hier1, hier2)
#> <Hierarchies> 
#>   no. hierarchies:  2 
#>   Poaceae / Poa / Poa annua 
#>   Felidae / Puma / Puma concolor

The “taxonomy” class

The taxonomy class stores unique taxon objects in a tree structure. Usually this kind of complex information would be the output of a file parsing function, but the code below shows how to construct a taxonomy object from scratch.

# define taxa
notoryctidae <- taxon(name = "Notoryctidae", rank = "family", id = 4479)
notoryctes <- taxon(name = "Notoryctes", rank = "genus", id = 4544)
typhlops <- taxon(name = "typhlops", rank = "species", id = 93036)
mammalia <- taxon(name = "Mammalia", rank = "class", id = 9681)
felidae <- taxon(name = "Felidae", rank = "family", id = 9681)
felis <- taxon(name = "Felis", rank = "genus", id = 9682)
catus <- taxon(name = "catus", rank = "species", id = 9685)
panthera <- taxon(name = "Panthera", rank = "genus", id = 146712)
tigris <- taxon(name = "tigris", rank = "species", id = 9696)
plantae <- taxon(name = "Plantae", rank = "kingdom", id = 33090)
solanaceae <- taxon(name = "Solanaceae", rank = "family", id = 4070)
solanum <- taxon(name = "Solanum", rank = "genus", id = 4107)
lycopersicum <- taxon(name = "lycopersicum", rank = "species", id = 49274)
tuberosum <- taxon(name = "tuberosum", rank = "species", id = 4113)
homo <- taxon(name = "homo", rank = "genus", id = 9605)
sapiens <- taxon(name = "sapiens", rank = "species", id = 9606)
hominidae <- taxon(name = "Hominidae", rank = "family", id = 9604)

# define hierarchies
tiger <- hierarchy(mammalia, felidae, panthera, tigris)
cat <- hierarchy(mammalia, felidae, felis, catus)
human <- hierarchy(mammalia, hominidae, homo, sapiens)
mole <- hierarchy(mammalia, notoryctidae, notoryctes, typhlops)
tomato <- hierarchy(plantae, solanaceae, solanum, lycopersicum)
potato <- hierarchy(plantae, solanaceae, solanum, tuberosum)

# make taxonomy
(tax <- taxonomy(tiger, cat, human, tomato, potato))
#> <Taxonomy>
#>   14 taxa: b. Mammalia ... n. lycopersicum, o. tuberosum
#>   14 edges: NA->b, NA->c, b->d ... h->l, i->m, j->n, j->o

Unlike the hierarchies class, each unique taxon object is only represented once in the taxonomy object. Each taxon has a corresponding entry in an edge list that encode how it is related to other taxa. This makes taxonomy more compact, but harder to manipulate using standard indexing. To make manipulation easier, there are methods for taxomomy that can provide indexes in a taxonomic context.

supertaxa

A “supertaxon” is a taxon of a coarser rank that encompasses the taxon of interest (e.g. “Homo” is a supertaxon of “sapiens”). The supertaxa function returns the supertaxa of all or a subset of the taxa in a taxonomy object.

supertaxa(tax)
#> $b
#> integer(0)
#> 
#> $c
#> integer(0)
#> 
#> $d
#> [1] 1
#> 
#> $e
#> [1] 1
#> 
#> $f
#> [1] 2
#> 
#> $g
#> [1] 3 1
#> 
#> $h
#> [1] 3 1
#> 
#> $i
#> [1] 4 1
#> 
#> $j
#> [1] 5 2
#> 
#> $k
#> [1] 6 3 1
#> 
#> $l
#> [1] 7 3 1
#> 
#> $m
#> [1] 8 4 1
#> 
#> $n
#> [1] 9 5 2
#> 
#> $o
#> [1] 9 5 2

By default, the taxon IDs for the supertaxa of all taxa are returned in the same order they appear in the edge list. Taxon IDs (character) or edge list indexes (integer) can be supplied to the subset option to only return information for some taxa.

supertaxa(tax, subset = "m")
#> $m
#> [1] 8 4 1

What is returned can be modified with the value option:

supertaxa(tax, subset = "m", value = "taxon_names")
#> $m
#>           i           e           b 
#>      "homo" "Hominidae"  "Mammalia"

supertaxa(tax, subset = "m", value = "taxon_ranks")
#> $m
#>        i        e        b 
#>  "genus" "family"  "class"

You can also subset based on a logical test:

supertaxa(tax, subset = taxon_ranks == "genus", value = "taxon_names")
#> $g
#>          d          b 
#>  "Felidae" "Mammalia" 
#> 
#> $h
#>          d          b 
#>  "Felidae" "Mammalia" 
#> 
#> $i
#>           e           b 
#> "Hominidae"  "Mammalia" 
#> 
#> $j
#>            f            c 
#> "Solanaceae"    "Plantae"

The subset and value work the same for most of the following functions as well. See tax$all_names() for what can be used with value.

subtaxa

The “subtaxa” of a taxon are all those of a finer rank encompassed by that taxon. For example, sapiens is a subtaxon of Homo. The subtaxa function returns all subtaxa for each taxon in a taxonomy object.

subtaxa(tax, value = "taxon_names")
#> $b
#>           d           g           k           h           l           e 
#>   "Felidae"  "Panthera"    "tigris"     "Felis"     "catus" "Hominidae" 
#>           i           m 
#>      "homo"   "sapiens" 
#> 
#> $c
#>              f              j              n              o 
#>   "Solanaceae"      "Solanum" "lycopersicum"    "tuberosum" 
#> 
#> $d
#>          g          k          h          l 
#> "Panthera"   "tigris"    "Felis"    "catus" 
#> 
#> $e
#>         i         m 
#>    "homo" "sapiens" 
#> 
#> $f
#>              j              n              o 
#>      "Solanum" "lycopersicum"    "tuberosum" 
#> 
#> $g
#>        k 
#> "tigris" 
#> 
#> $h
#>       l 
#> "catus" 
#> 
#> $i
#>         m 
#> "sapiens" 
#> 
#> $j
#>              n              o 
#> "lycopersicum"    "tuberosum" 
#> 
#> $k
#> named character(0)
#> 
#> $l
#> named character(0)
#> 
#> $m
#> named character(0)
#> 
#> $n
#> named character(0)
#> 
#> $o
#> named character(0)

roots

We call taxa that have no supertaxa “roots”. The roots function returns these taxa.

roots(tax, value = "taxon_names")
#>          b          c 
#> "Mammalia"  "Plantae"

leaves

We call taxa without any subtaxa “leaves”. The leaves function returns these taxa.

leaves(tax, value = "taxon_names")
#>              k              l              m              n              o 
#>       "tigris"        "catus"      "sapiens" "lycopersicum"    "tuberosum"

other functions

There are many other functions to interact with taxonomy object, such as stems and n_subtaxa, but these will not be described here for now.

The “taxmap” class

The taxmap class is used to store any number of tables, lists, or vectors associated with taxa. It is basically the same as the taxonomy class, but with the following additions:

info <- data.frame(name = c("tiger", "cat", "mole", "human", "tomato", "potato"),
                   n_legs = c(4, 4, 4, 2, 0, 0),
                   dangerous = c(TRUE, FALSE, FALSE, TRUE, FALSE, FALSE))

phylopic_ids <- c("e148eabb-f138-43c6-b1e4-5cda2180485a",
                  "12899ba0-9923-4feb-a7f9-758c3c7d5e13",
                  "11b783d5-af1c-4f4e-8ab5-a51470652b47",
                  "9fae30cd-fb59-4a81-a39c-e1826a35f612",
                  "b6400f39-345a-4711-ab4f-92fd4e22cb1a",
                  "63604565-0406-460b-8cb8-1abe954b3f3a")

foods <- list(c("mammals", "birds"),
              c("cat food", "mice"),
              c("insects"),
              c("Most things, but especially anything rare or expensive"),
              c("light", "dirt"),
              c("light", "dirt"))

reaction <- function(x) {
  ifelse(x$data$info$dangerous,
         paste0("Watch out! That ", x$data$info$name, " might attack!"),
         paste0("No worries; its just a ", x$data$info$name, "."))
}

my_taxmap <- taxmap(tiger, cat, mole, human, tomato, potato,
                    data = list(info = info,
                                phylopic_ids = phylopic_ids,
                                foods = foods),
                    funcs = list(reaction = reaction))

In most functions that work with taxmap objects, the names of list/vector datasets, table columns, or functions can be used as if they were separate variables on their own. In the case of functions, instead of returning the function itself, the results of the functions are returned. To see what variables can be used this way, use all_names.

all_names(my_taxmap)
#>         taxon_names           taxon_ids       taxon_indexes 
#>       "taxon_names"         "taxon_ids"     "taxon_indexes" 
#>         n_supertaxa           n_subtaxa         n_subtaxa_1 
#>       "n_supertaxa"         "n_subtaxa"       "n_subtaxa_1" 
#>         taxon_ranks             is_root             is_stem 
#>       "taxon_ranks"           "is_root"           "is_stem" 
#>           is_branch             is_leaf      data$info$name 
#>         "is_branch"           "is_leaf"              "name" 
#>    data$info$n_legs data$info$dangerous   data$phylopic_ids 
#>            "n_legs"         "dangerous"      "phylopic_ids" 
#>          data$foods      funcs$reaction 
#>             "foods"          "reaction"

For example using my_taxmap$data$info$n_legs or n_legs will have the same effect inside manipulation functions like filter_taxa described below. To get the values of these variables, use get_data.

get_data(my_taxmap)
#> $taxon_names
#>              b              c              d              e              f 
#>     "Mammalia"      "Plantae"      "Felidae" "Notoryctidae"    "Hominidae" 
#>              g              h              i              j              k 
#>   "Solanaceae"     "Panthera"        "Felis"   "Notoryctes"         "homo" 
#>              l              m              n              o              p 
#>      "Solanum"       "tigris"        "catus"     "typhlops"      "sapiens" 
#>              q              r 
#> "lycopersicum"    "tuberosum" 
#> 
#> $taxon_ids
#>   b   c   d   e   f   g   h   i   j   k   l   m   n   o   p   q   r 
#> "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" 
#> 
#> $taxon_indexes
#>  b  c  d  e  f  g  h  i  j  k  l  m  n  o  p  q  r 
#>  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 
#> 
#> $n_supertaxa
#> b c d e f g h i j k l m n o p q r 
#> 0 0 1 1 1 1 2 2 2 2 2 3 3 3 3 3 3 
#> 
#> $n_subtaxa
#>  b  c  d  e  f  g  h  i  j  k  l  m  n  o  p  q  r 
#> 11  4  4  2  2  3  1  1  1  1  2  0  0  0  0  0  0 
#> 
#> $n_subtaxa_1
#> b c d e f g h i j k l m n o p q r 
#> 3 1 2 1 1 1 1 1 1 1 2 0 0 0 0 0 0 
#> 
#> $taxon_ranks
#>         b         c         d         e         f         g         h 
#>   "class" "kingdom"  "family"  "family"  "family"  "family"   "genus" 
#>         i         j         k         l         m         n         o 
#>   "genus"   "genus"   "genus"   "genus" "species" "species" "species" 
#>         p         q         r 
#> "species" "species" "species" 
#> 
#> $is_root
#>     b     c     d     e     f     g     h     i     j     k     l     m 
#>  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 
#>     n     o     p     q     r 
#> FALSE FALSE FALSE FALSE FALSE 
#> 
#> $is_stem
#>     b     c     d     e     f     g     h     i     j     k     l     m 
#> FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 
#>     n     o     p     q     r 
#> FALSE FALSE FALSE FALSE FALSE 
#> 
#> $is_branch
#>     b     c     d     e     f     g     h     i     j     k     l     m 
#> FALSE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE 
#>     n     o     p     q     r 
#> FALSE FALSE FALSE FALSE FALSE 
#> 
#> $is_leaf
#>     b     c     d     e     f     g     h     i     j     k     l     m 
#> FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE 
#>     n     o     p     q     r 
#>  TRUE  TRUE  TRUE  TRUE  TRUE 
#> 
#> $name
#>      m      n      o      p      q      r 
#>  tiger    cat   mole  human tomato potato 
#> Levels: cat human mole potato tiger tomato
#> 
#> $n_legs
#> m n o p q r 
#> 4 4 4 2 0 0 
#> 
#> $dangerous
#>     m     n     o     p     q     r 
#>  TRUE FALSE FALSE  TRUE FALSE FALSE 
#> 
#> $phylopic_ids
#>                                      m 
#> "e148eabb-f138-43c6-b1e4-5cda2180485a" 
#>                                      n 
#> "12899ba0-9923-4feb-a7f9-758c3c7d5e13" 
#>                                      o 
#> "11b783d5-af1c-4f4e-8ab5-a51470652b47" 
#>                                      p 
#> "9fae30cd-fb59-4a81-a39c-e1826a35f612" 
#>                                      q 
#> "b6400f39-345a-4711-ab4f-92fd4e22cb1a" 
#>                                      r 
#> "63604565-0406-460b-8cb8-1abe954b3f3a" 
#> 
#> $foods
#> $foods$m
#> [1] "mammals" "birds"  
#> 
#> $foods$n
#> [1] "cat food" "mice"    
#> 
#> $foods$o
#> [1] "insects"
#> 
#> $foods$p
#> [1] "Most things, but especially anything rare or expensive"
#> 
#> $foods$q
#> [1] "light" "dirt" 
#> 
#> $foods$r
#> [1] "light" "dirt" 
#> 
#> 
#> $reaction
#> [1] "Watch out! That tiger might attack!"
#> [2] "No worries; its just a cat."        
#> [3] "No worries; its just a mole."       
#> [4] "Watch out! That human might attack!"
#> [5] "No worries; its just a tomato."     
#> [6] "No worries; its just a potato."

Note how “taxon_names” and “dangerous” are used below.

Filtering

In addition to all of the functions like subtaxa that work with taxonomy, taxmap has a set of functions to manipulate data in a taxonomic context using functions based on dplyr. Like many operations on taxmap objects, there are a pair of functions that modify the taxa as well as the associated data, which we call “observations”. The filter_taxa and filter_obs functions are an example of such a pair that can filter taxa and observations respectively. For example, we can use filter_taxa to subset all taxa with a name starting with “t”:

filter_taxa(my_taxmap, startsWith(taxon_names, "t"))
#> <Taxmap>
#>   3 taxa: m. tigris, o. typhlops, r. tuberosum
#>   3 edges: NA->m, NA->o, NA->r
#>   3 data sets:
#>     info:
#>       # A tibble: 3 x 4
#>           name n_legs dangerous taxon_id
#>         <fctr>  <dbl>     <lgl>    <chr>
#>       1  tiger      4      TRUE        m
#>       2   mole      4     FALSE        o
#>       3 potato      0     FALSE        r
#>     phylopic_ids:  e148eabb-f138-43c6-b1e4-5cda2180485a ... 63604565-0406-460b-8cb8-1abe954b3f3a
#>     foods: a list with 3 items
#>   1 functions:
#>  reaction

There can be any number of filters that resolve to TRUE/FALSE vectors, taxon ids, or edge list indexes.

filter_taxa(my_taxmap, startsWith(taxon_names, "t"), "r")

There are many options for filter_taxa that make it very flexible. For example, the supertaxa option can make all the supertaxa of selected taxa be preserved.

filter_taxa(my_taxmap, startsWith(taxon_names, "t"), supertaxa = TRUE)
#> <Taxmap>
#>   11 taxa: m. tigris ... g. Solanaceae, c. Plantae
#>   11 edges: h->m, j->o, l->r, d->h ... b->e, g->l, c->g, NA->c
#>   3 data sets:
#>     info:
#>       # A tibble: 6 x 4
#>           name n_legs dangerous taxon_id
#>         <fctr>  <dbl>     <lgl>    <chr>
#>       1  tiger      4      TRUE        m
#>       2    cat      4     FALSE        d
#>       3   mole      4     FALSE        o
#>       # ... with 3 more rows
#>     phylopic_ids:  e148eabb-f138-43c6-b1e4-5cda2180485a ... 63604565-0406-460b-8cb8-1abe954b3f3a
#>     foods: a list with 6 items
#>   1 functions:
#>  reaction

The filter_obs function works in a similar way, but subsets observations in my_taxmap$data.

filter_obs(my_taxmap, "info", dangerous == TRUE)
#> <Taxmap>
#>   17 taxa: b. Mammalia ... q. lycopersicum, r. tuberosum
#>   17 edges: NA->b, NA->c, b->d ... j->o, k->p, l->q, l->r
#>   3 data sets:
#>     info:
#>       # A tibble: 2 x 4
#>           name n_legs dangerous taxon_id
#>         <fctr>  <dbl>     <lgl>    <chr>
#>       1  tiger      4      TRUE        m
#>       2  human      2      TRUE        p
#>     phylopic_ids:  e148eabb-f138-43c6-b1e4-5cda2180485a ... 63604565-0406-460b-8cb8-1abe954b3f3a
#>     foods: a list with 6 items
#>   1 functions:
#>  reaction

You can choose to filter out taxa whose observations did not pass the filter as well:

filter_obs(my_taxmap, "info", dangerous == TRUE, drop_taxa = TRUE)
#> <Taxmap>
#>   7 taxa: b. Mammalia, d. Felidae ... m. tigris, p. sapiens
#>   7 edges: NA->b, b->d, b->f, d->h, f->k, h->m, k->p
#>   3 data sets:
#>     info:
#>       # A tibble: 2 x 4
#>           name n_legs dangerous taxon_id
#>         <fctr>  <dbl>     <lgl>    <chr>
#>       1  tiger      4      TRUE        m
#>       2  human      2      TRUE        p
#>     phylopic_ids:  e148eabb-f138-43c6-b1e4-5cda2180485a ... 63604565-0406-460b-8cb8-1abe954b3f3a
#>     foods: a list with 6 items
#>   1 functions:
#>  reaction

Sampling

The functions sample_n_obs and sample_n_taxa are similar to filter_obs and filter_taxa, except taxa/observations are chosen randomly. All of the options of the “filter_” functions are available to the “sample_” functions

set.seed(1)
sample_n_taxa(my_taxmap, 3)
#> <Taxmap>
#>   3 taxa: g. Solanaceae, i. Felis, m. tigris
#>   3 edges: NA->g, NA->i, NA->m
#>   3 data sets:
#>     info:
#>       # A tibble: 4 x 4
#>           name n_legs dangerous taxon_id
#>         <fctr>  <dbl>     <lgl>    <chr>
#>       1  tiger      4      TRUE        m
#>       2    cat      4     FALSE        i
#>       3 tomato      0     FALSE        g
#>       # ... with 1 more rows
#>     phylopic_ids:  e148eabb-f138-43c6-b1e4-5cda2180485a ... 63604565-0406-460b-8cb8-1abe954b3f3a
#>     foods: a list with 4 items
#>   1 functions:
#>  reaction
set.seed(1)
sample_n_taxa(my_taxmap, 3, supertaxa = TRUE)
#> <Taxmap>
#>   7 taxa: g. Solanaceae, i. Felis ... b. Mammalia, h. Panthera
#>   7 edges: c->g, d->i, h->m, NA->c, b->d, NA->b, d->h
#>   3 data sets:
#>     info:
#>       # A tibble: 6 x 4
#>           name n_legs dangerous taxon_id
#>         <fctr>  <dbl>     <lgl>    <chr>
#>       1  tiger      4      TRUE        m
#>       2    cat      4     FALSE        i
#>       3   mole      4     FALSE        b
#>       # ... with 3 more rows
#>     phylopic_ids:  e148eabb-f138-43c6-b1e4-5cda2180485a ... 63604565-0406-460b-8cb8-1abe954b3f3a
#>     foods: a list with 6 items
#>   1 functions:
#>  reaction

Adding columns

Adding columns to tabular datasets is done using mutate_obs.

mutate_obs(my_taxmap, "info",
           new_col = "Im new",
           newer_col = paste0(new_col, "er!"))
#> <Taxmap>
#>   17 taxa: b. Mammalia ... q. lycopersicum, r. tuberosum
#>   17 edges: NA->b, NA->c, b->d ... j->o, k->p, l->q, l->r
#>   3 data sets:
#>     info:
#>       # A tibble: 6 x 6
#>           name n_legs dangerous taxon_id new_col newer_col
#>         <fctr>  <dbl>     <lgl>    <chr>   <chr>     <chr>
#>       1  tiger      4      TRUE        m  Im new Im newer!
#>       2    cat      4     FALSE        n  Im new Im newer!
#>       3   mole      4     FALSE        o  Im new Im newer!
#>       # ... with 3 more rows
#>     phylopic_ids:  e148eabb-f138-43c6-b1e4-5cda2180485a ... 63604565-0406-460b-8cb8-1abe954b3f3a
#>     foods: a list with 6 items
#>   1 functions:
#>  reaction

Subsetting columns

Subsetting columns in tabular datasets is done using select_obs.

# Selecting a column by name
select_obs(my_taxmap, "info", dangerous)
#> <Taxmap>
#>   17 taxa: b. Mammalia ... q. lycopersicum, r. tuberosum
#>   17 edges: NA->b, NA->c, b->d ... j->o, k->p, l->q, l->r
#>   3 data sets:
#>     info:
#>       # A tibble: 6 x 2
#>         taxon_id dangerous
#>            <chr>     <lgl>
#>       1        m      TRUE
#>       2        n     FALSE
#>       3        o     FALSE
#>       # ... with 3 more rows
#>     phylopic_ids:  e148eabb-f138-43c6-b1e4-5cda2180485a ... 63604565-0406-460b-8cb8-1abe954b3f3a
#>     foods: a list with 6 items
#>   1 functions:
#>  reaction

# Selecting a column by index
select_obs(my_taxmap, "info", 3)
#> <Taxmap>
#>   17 taxa: b. Mammalia ... q. lycopersicum, r. tuberosum
#>   17 edges: NA->b, NA->c, b->d ... j->o, k->p, l->q, l->r
#>   3 data sets:
#>     info:
#>       # A tibble: 6 x 2
#>         taxon_id dangerous
#>            <chr>     <lgl>
#>       1        m      TRUE
#>       2        n     FALSE
#>       3        o     FALSE
#>       # ... with 3 more rows
#>     phylopic_ids:  e148eabb-f138-43c6-b1e4-5cda2180485a ... 63604565-0406-460b-8cb8-1abe954b3f3a
#>     foods: a list with 6 items
#>   1 functions:
#>  reaction

# Selecting a column by regular expressions
select_obs(my_taxmap, "info", matches("^dange"))
#> <Taxmap>
#>   17 taxa: b. Mammalia ... q. lycopersicum, r. tuberosum
#>   17 edges: NA->b, NA->c, b->d ... j->o, k->p, l->q, l->r
#>   3 data sets:
#>     info:
#>       # A tibble: 6 x 2
#>         taxon_id dangerous
#>            <chr>     <lgl>
#>       1        m      TRUE
#>       2        n     FALSE
#>       3        o     FALSE
#>       # ... with 3 more rows
#>     phylopic_ids:  e148eabb-f138-43c6-b1e4-5cda2180485a ... 63604565-0406-460b-8cb8-1abe954b3f3a
#>     foods: a list with 6 items
#>   1 functions:
#>  reaction

Sorting

Sorting the edge list and observations is done using arrage_taxa and arrange_obs.

arrange_taxa(my_taxmap, taxon_names)
#> <Taxmap>
#>   17 taxa: n. catus, d. Felidae ... r. tuberosum, o. typhlops
#>   17 edges: i->n, b->d, d->i, b->f ... g->l, h->m, l->r, j->o
#>   3 data sets:
#>     info:
#>       # A tibble: 6 x 4
#>           name n_legs dangerous taxon_id
#>         <fctr>  <dbl>     <lgl>    <chr>
#>       1  tiger      4      TRUE        m
#>       2    cat      4     FALSE        n
#>       3   mole      4     FALSE        o
#>       # ... with 3 more rows
#>     phylopic_ids:  e148eabb-f138-43c6-b1e4-5cda2180485a ... 63604565-0406-460b-8cb8-1abe954b3f3a
#>     foods: a list with 6 items
#>   1 functions:
#>  reaction
arrange_obs(my_taxmap, "info", name)
#> <Taxmap>
#>   17 taxa: b. Mammalia ... q. lycopersicum, r. tuberosum
#>   17 edges: NA->b, NA->c, b->d ... j->o, k->p, l->q, l->r
#>   3 data sets:
#>     info:
#>       # A tibble: 6 x 4
#>           name n_legs dangerous taxon_id
#>         <fctr>  <dbl>     <lgl>    <chr>
#>       1    cat      4     FALSE        n
#>       2  human      2      TRUE        p
#>       3   mole      4     FALSE        o
#>       # ... with 3 more rows
#>     phylopic_ids:  e148eabb-f138-43c6-b1e4-5cda2180485a ... 63604565-0406-460b-8cb8-1abe954b3f3a
#>     foods: a list with 6 items
#>   1 functions:
#>  reaction

Parsing data

The taxmap class has the ability to contain and manipulate very complex data. However, this can make it difficult to parse the data into a taxmap object. For this reason there are three functions to help creating taxmap objects from nearly any kind of data that a taxonomy can be associated with and derived from. The figure below shows simplified versions of how to create taxmap objects from different types of data in different formats.