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taxa

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:

  • Classes that are concerned only with taxonomic information: taxon, taxonomy, hierarchy, etc.
  • A class called taxmap that is concerned with combining taxonomic data with user-defined data of any type (e.g. molecular sequences, abundance counts etc.)

Diagram of class concepts for taxa classes:

Install

Development version from GitHub

devtools::install_github("ropensci/taxa")

library("taxa")

The classes

Minor component classes

There 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:

  • A list called data that stores arbitrary user data associated with taxa
  • A list called funcs that stores user defined functions
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

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: b. Mammalia ... q. lycopersicum, r. tuberosum
#>   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.

The parse_tax_data and lookup_tax_data have, in addition to the functionality above, the ability to include additional data sets that are somehow associated with the source datasets (e.g. share a common identifier). Elements in these datasets will be assigned the taxa defined in the source data, so functions like filter_taxa and filter_obs will work on all of the dataset at once.

For more information

This vignettte is meant to be just an outline of what taxa can do. In the future, we plan to release additional, in-depth vignettes for specific topics. More informaiton for specific functions and examples can be found on their man pages by type the name of the function prefixed by a ? in the consol of an R session. For example, ?filter_taxa will pull up the help page for filter_taxa.

Use cases

  • use in binomen:
    • if this pkg does classes, binomen can focus on verbs, e.g., manipulating taxonomic classes, doing split-apply-combine type things
  • use in taxize:
    • as we don't want to break things, probably ideal to have coercion fxns, e.g., as.taxon(), which will convert e.g., the output of get_uid() to a taxa taxonomic class, which we can then go downstream and do things with (i.e., whatever we build on top of the classes)
    • Or we could even have output of get_*() functions do coercion to taxa classes on output since they are just simple S3 classes without print methods right now
  • use in metacoder: This will eventually replace the similar classes used in metacoder.

Contributors

Comments and contributions

We welcome comments, criticisms, and especially contributions! GitHub issues are the preferred way to report bugs, ask questions, or request new features. You can submit issues here:

https://github.com/ropensci/taxa/issues

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Install

install.packages('taxa')

Monthly Downloads

286

Version

0.1.0

License

MIT + file LICENSE

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Maintainer

Scott Chamberlain

Last Published

July 16th, 2017

Functions in taxa (0.1.0)

contains

dplyr select_helpers
convert_base

Converts decimal numbers to other bases
arrange_obs

arrange_taxa

count_capture_groups

Count capture groups
data_used

Get values of data used in expressions
ex_hierarchy1

An example Hierarchy object
ex_hierarchy2

An example Hierarchy object
all_functions

Get list of usable functions
all_names

database_list

Database list
ends_with

dplyr select_helpers
%>%

magrittr forward-pipe operator
everything

dplyr select_helpers
ex_hierarchies

An example hierarchies object
get_dots_or_list

Get input from dots or list
get_sort_var

Get a vector from a vector/list/table to be used in mapping
ex_taxonomy

An example Taxonomy object
extract_tax_data

Extracts taxonomy info from vectors with regex
get_data

Get data in a taxmap object by name
get_database_name

Return name of database
filtering-helpers

Taxonomic filtering helpers
format_taxon_subset

Format taxon subset value
hierarchy

The Hierarchy class
lookup_tax_data

Convert one or more data sets to taxmap
map_data

Create a mapping between two variables
multi_sep_split

Like strsplit, but with multiple separators
mutate_obs

is_root

Test if taxa are roots
is_stem

Test if taxa are stems
n_supertaxa

Get number of supertaxa
check_for_pkg

check for packages
check_taxmap_data

Check dataset format
ex_hierarchy3

An example Hierarchy object
ex_taxmap

An example taxmap object
hierarchies

is_branch

Test if taxa are branches
is_leaf

Test if taxa are leaves
n_subtaxa

Get number of subtaxa
name_classifications

Get classifications of taxa
names_used

Get names of data used in expressions
num_range

dplyr select_helpers
id_classifications

Get classifications of taxa
map_unique

Run a function on unique values of a iterable
matches

dplyr select_helpers
obs

Get data indexes associated with taxa
span

Span taxa
starts_with

dplyr select_helpers
supertaxa_apply

Apply function to supertaxa of each taxon
taxa-package

taxa
taxon_names

Get taxon names
taxon_rank

Taxon rank class
validate_regex_key_pair

Check a regex-key pair
validate_regex_match

Check that all match input
parse_tax_data

Convert one or more data sets to taxmap
pick

Pick taxa
sample_n_taxa

select_obs

subtaxa_apply

Apply function to subtaxa of each taxon
n_subtaxa_1

Get number of subtaxa
pop

Pop taxa out
print_item

Print a table
sample_frac_taxa

obs_apply

Apply function to observations per taxon
roots

Get root taxa
sample_frac_obs

taxon

Taxon class
filter_obs

Filter observations with a list of conditions
filter_taxa

Filter taxa with a list of conditions
leaves

Get leaf taxa
supertaxa

Get all supertaxa of a taxon
taxon_indexes

Get taxon indexes
taxon_name

Taxon name class
validate_taxmap_data

Convert data input for Taxamp
limited_print

Print a subset of a character vector
n_obs

n_obs_1

one_of

dplyr select_helpers
ranks_ref

Lookup-table for IDs of taxonomic ranks
replace_taxon_ids

Replace taxon ids
taxa

A class for multiple taxon objects
taxon_database

Taxonomy database class
taxon_id

Taxon ID class
taxon_ids

Get taxon IDs
sample_n_obs

stems

Get stem taxa
subtaxa

Get subtaxa
parse_possibly_named_logical

used to parse inputs to drop_obs and reassign_obs
validate_taxmap_funcs

Validate funcs input for Taxamp
taxmap

Taxmap class
taxon_ranks

Get taxon ranks
taxonomy

Taxonomy class
transmute_obs

unique_mapping

Get indexes of a unique set of the input