taxize tutorial
for v0.9.0
taxize is a taxonomic toolbelt for R. taxize wraps APIs for a large suite of taxonomic databases availab on the web.
Installation
First, install and load taxize into the R session.
install.packages("taxize")
Or, install development version from GitHub
if (!require("devtools")) install.packages("devtools")
devtools::install_github("ropensci/taxize")
library("taxize")
Usage
Resolve taxonomic name
This is a common task in biology. We often have a list of species names and we want to know a) if we have the most up to date names, b) if our names are spelled correctly, and c) the scientific name for a common name. One way to resolve names is via the Global Names Resolver (GNR) service provided by the Encyclopedia of Life. Here, we are searching for two misspelled names:
temp <- gnr_resolve(names = c("Helianthos annus", "Homo saapiens"))
head(temp)
#> user_supplied_name submitted_name matched_name
#> 1 Helianthos annus Helianthos annus Helianthus annus
#> 2 Helianthos annus Helianthos annus Helianthus annus L.
#> 3 Helianthos annus Helianthos annus Helianthus annus
#> 4 Helianthos annus Helianthos annus Helianthus annus
#> 5 Helianthos annus Helianthos annus Helianthus annuus L.
#> 6 Helianthos annus Helianthos annus Helianthus annuus L.
#> data_source_title score
#> 1 EOL 0.75
#> 2 EOL 0.75
#> 3 uBio NameBank 0.75
#> 4 Open Tree of Life Reference Taxonomy 0.75
#> 5 Catalogue of Life 0.75
#> 6 ITIS 0.75
The correct spellings are Helianthus annuus and Homo sapiens.
Another common use case is when there are many synonyms for a species. In this example, we have three synonyms of the currently accepted name for a species.
mynames <- c("Helianthus annuus ssp. jaegeri", "Helianthus annuus ssp. lenticularis", "Helianthus annuus ssp. texanus")
(tsn <- get_tsn(mynames, accepted = FALSE))
[1] "525928" "525929" "525930"
attr(,"match")
[1] "found" "found" "found"
attr(,"multiple_matches")
[1] FALSE FALSE FALSE
attr(,"pattern_match")
[1] FALSE FALSE FALSE
attr(,"uri")
[1] "http://www.itis.gov/servlet/SingleRpt/SingleRpt?search_topic=TSN&search_value=525928"
[2] "http://www.itis.gov/servlet/SingleRpt/SingleRpt?search_topic=TSN&search_value=525929"
[3] "http://www.itis.gov/servlet/SingleRpt/SingleRpt?search_topic=TSN&search_value=525930"
attr(,"class")
[1] "tsn"
lapply(tsn, itis_acceptname)
[[1]]
submittedtsn acceptedname acceptedtsn author
1 525928 Helianthus annuus 36616 L.
[[2]]
submittedtsn acceptedname acceptedtsn author
1 525929 Helianthus annuus 36616 L.
[[3]]
submittedtsn acceptedname acceptedtsn author
1 525930 Helianthus annuus 36616 L.
Retrieve higher taxonomic names
Another task biologists often face is getting higher taxonomic names for a taxa list. Having the higher taxonomy allows you to put into context the relationships of your species list. For example, you may find out that species A and species B are in Family C, which may lead to some interesting insight, as opposed to not knowing that Species A and B are closely related. This also makes it easy to aggregate/standardize data to a specific taxonomic level (e.g., family level) or to match data to other databases with different taxonomic resolution (e.g., trait databases).
A number of data sources in taxize provide the capability to retrieve higher taxonomic names, but we will highlight two of the more useful ones: Integrated Taxonomic Information System (ITIS) and National Center for Biotechnology Information (NCBI). First, we’ll search for two species, *Abies procera} and Pinus contorta within ITIS.
specieslist <- c("Abies procera","Pinus contorta")
classification(specieslist, db = 'itis')
#> tsn target
#> 1 183327 Pinus contorta
#> 2 183332 Pinus contorta ssp. bolanderi
#> 3 822698 Pinus contorta ssp. contorta
#> 4 183329 Pinus contorta ssp. latifolia
#> 5 183330 Pinus contorta ssp. murrayana
#> 6 529672 Pinus contorta var. bolanderi
#> 7 183328 Pinus contorta var. contorta
#> 8 529673 Pinus contorta var. latifolia
#> 9 529674 Pinus contorta var. murrayana
#> commonNames
#> 1 scrub pine,shore pine,tamarack pine,lodgepole pine
#> 2 Bolander's beach pine
#> 3 NA
#> 4 black pine,Rocky Mountain lodgepole pine
#> 5 tamarack pine,Sierra lodgepole pine
#> 6 Bolander beach pine
#> 7 coast pine,lodgepole pine,beach pine,shore pine
#> 8 tall lodgepole pine,lodgepole pine,Rocky Mountain lodgepole pine
#> 9 Murray's lodgepole pine,Sierra lodgepole pine,tamarack pine
#> nameUsage
#> 1 accepted
#> 2 not accepted
#> 3 not accepted
#> 4 not accepted
#> 5 not accepted
#> 6 accepted
#> 7 accepted
#> 8 accepted
#> 9 accepted
#> $`Abies procera`
#> name rank id
#> 1 Plantae kingdom 202422
#> 2 Viridiplantae subkingdom 954898
#> 3 Streptophyta infrakingdom 846494
#> 4 Embryophyta superdivision 954900
#> 5 Tracheophyta division 846496
#> 6 Spermatophytina subdivision 846504
#> 7 Pinopsida class 500009
#> 8 Pinidae subclass 954916
#> 9 Pinales order 500028
#> 10 Pinaceae family 18030
#> 11 Abies genus 18031
#> 12 Abies procera species 181835
#>
#> $`Pinus contorta`
#> name rank id
#> 1 Plantae kingdom 202422
#> 2 Viridiplantae subkingdom 954898
#> 3 Streptophyta infrakingdom 846494
#> 4 Embryophyta superdivision 954900
#> 5 Tracheophyta division 846496
#> 6 Spermatophytina subdivision 846504
#> 7 Pinopsida class 500009
#> 8 Pinidae subclass 954916
#> 9 Pinales order 500028
#> 10 Pinaceae family 18030
#> 11 Pinus genus 18035
#> 12 Pinus contorta species 183327
#>
#> attr(,"class")
#> [1] "classification"
#> attr(,"db")
#> [1] "itis"
It turns out both species are in the family Pinaceae. You can also get this type of information from the NCBI by doing classification(specieslist, db = 'ncbi').
Instead of a full classification, you may only want a single name, say a family name for your species of interest. The function *tax_name} is built just for this purpose. As with the classification function you can specify the data source with the db argument, either ITIS or NCBI.
tax_name(query = "Helianthus annuus", get = "family", db = "ncbi")
#> db query family
#> 1 ncbi Helianthus annuus Asteraceae
I may happen that a data source does not provide information on the queried species, than one could take the result from another source and union the results from the different sources.
Interactive name selection
As mentioned most databases use a numeric code to reference a species. A general workflow in taxize is: Retrieve Code for the queried species and then use this code to query more data/information.
Below are a few examples. When you run these examples in R, you are presented with a command prompt asking for the row that contains the name you would like back; that output is not printed below for brevity. In this example, the search term has many matches. The function returns a data frame of the matches, and asks for the user to input what row number to accept.
get_uid(sciname = "Pinus")
#> status rank division scientificname commonname uid genus
#> 1 active subgenus seed plants Pinus hard pines 139271
#> 2 active genus seed plants Pinus 3337
#> species subsp modificationdate
#> 1 2015/09/16 00:00
#> 2 2004/09/10 00:00
#> [1] "139271"
#> attr(,"class")
#> [1] "uid"
#> attr(,"match")
#> [1] "found"
#> attr(,"multiple_matches")
#> [1] TRUE
#> attr(,"pattern_match")
#> [1] FALSE
#> attr(,"uri")
#> [1] "https://www.ncbi.nlm.nih.gov/taxonomy/139271"
In another example, you can pass in a long character vector of taxonomic names (although this one is rather short for demo purposes):
splist <- c("annona cherimola", 'annona muricata', "quercus robur")
get_tsn(searchterm = splist, searchtype = "scientific")
#> tsn target commonNames nameUsage
#> 1 19405 Quercus robur English oak accepted
#> 2 845209 Quercus robur f. fastigiata NA not accepted
#> [1] "506198" "18098" "19405"
#> attr(,"match")
#> [1] "found" "found" "found"
#> attr(,"multiple_matches")
#> [1] FALSE FALSE TRUE
#> attr(,"pattern_match")
#> [1] FALSE FALSE FALSE
#> attr(,"uri")
#> [1] "http://www.itis.gov/servlet/SingleRpt/SingleRpt?search_topic=TSN&search_value=506198"
#> [2] "http://www.itis.gov/servlet/SingleRpt/SingleRpt?search_topic=TSN&search_value=18098"
#> [3] "http://www.itis.gov/servlet/SingleRpt/SingleRpt?search_topic=TSN&search_value=19405"
#> attr(,"class")
#> [1] "tsn"
There are functions for many other sources
get_boldid()get_colid()get_eolid()get_gbifid()get_nbnid()get_tpsid()
Sometimes with these functions you get a lot of data back. In these cases you may want to limit your choices. Soon we will incorporate the ability to filter using regex to limit matches, but for now, we have a new parameter, rows, which lets you select certain rows. For example, you can select the first row of each given name, which means there is no interactive component:
get_nbnid(c("Zootoca vivipara","Pinus contorta"), rows = 1)
#> [1] "NHMSYS0001706186" "NBNSYS0000004786"
#> attr(,"class")
#> [1] "nbnid"
#> attr(,"match")
#> [1] "found" "found"
#> attr(,"multiple_matches")
#> [1] TRUE TRUE
#> attr(,"pattern_match")
#> [1] FALSE FALSE
#> attr(,"uri")
#> [1] "https://species.nbnatlas.org/species/NHMSYS0001706186"
#> [2] "https://species.nbnatlas.org/species/NBNSYS0000004786"
Or you can select a range of rows
get_nbnid(c("Zootoca vivipara","Pinus contorta"), rows = 1:3)
#> nbnid scientificName rank
#> 1 NHMSYS0001706186 Zootoca vivipara species
#> 2 NHMSYS0020784960 Zootoca vivipara subsp. pannonica subspecies
#> 3 NHMSYS0020233881 Chaetozone vivipara species
#> taxonomicStatus
#> 1 accepted
#> 2 accepted
#> 3 accepted
#> nbnid scientificName rank taxonomicStatus
#> 1 NBNSYS0000004786 Pinus contorta species accepted
#> 2 NHMSYS0000494858 Pinus contorta var. murrayana variety accepted
#> 3 NHMSYS0000494848 Pinus contorta var. contorta variety accepted
#> [1] "NHMSYS0001706186" "NBNSYS0000004786"
#> attr(,"class")
#> [1] "nbnid"
#> attr(,"match")
#> [1] "found" "found"
#> attr(,"multiple_matches")
#> [1] TRUE TRUE
#> attr(,"pattern_match")
#> [1] FALSE FALSE
#> attr(,"uri")
#> [1] "https://species.nbnatlas.org/species/NHMSYS0001706186"
#> [2] "https://species.nbnatlas.org/species/NBNSYS0000004786"
In addition, in case you don’t want to do interactive name selection in the case where there are a lot of names, you can get all data back with functions of the form, e.g., get_tsn_(), and likewise for other data sources. For example:
out <- get_nbnid_("Poa annua")
NROW(out$`Poa annua`)
#> [1] 25
That’s a lot of data, so we can get only certain rows back
get_nbnid_("Poa annua", rows = 1:10)
#> $`Poa annua`
#> guid scientificName rank taxonomicStatus
#> 1 NBNSYS0000002544 Poa annua species accepted
#> 2 NBNSYS0200003392 Triumfetta annua species accepted
#> 3 NBNSYS0000002918 Lunaria annua species accepted
#> 4 NBNSYS0200001901 Bellis annua species accepted
#> 5 NBNSYS0000033325 Artemisia annua species accepted
#> 6 NHMSYS0000456951 Carrichtera annua species accepted
#> 7 NBNSYS0200002555 Lonas annua species accepted
#> 8 NBNSYS0200002917 Poa ampla species accepted
#> 9 NBNSYS0200002926 Poa schimperiana species accepted
#> 10 NBNSYS0200002923 Poa leptoclada species accepted
Coerce numerics/alphanumerics to taxon IDs
We’ve also introduced in v0.5 the ability to coerce numerics and alphanumerics to taxonomic ID classes that are usually only retrieved via get_*() functions.
For example, adfafd
as.gbifid(get_gbifid("Poa annua")) # already a uid, returns the same
#> gbifid scientificname rank status matchtype
#> 1 2704179 Poa annua L. species ACCEPTED EXACT
#> 2 8422205 Poa annua Cham. & Schltdl. species SYNONYM EXACT
#> 3 7730008 Poa annua Steud. species DOUBTFUL EXACT
#> [1] "2704179"
#> attr(,"class")
#> [1] "gbifid"
#> attr(,"match")
#> [1] "found"
#> attr(,"multiple_matches")
#> [1] TRUE
#> attr(,"pattern_match")
#> [1] FALSE
#> attr(,"uri")
#> [1] "http://www.gbif.org/species/2704179"
as.gbifid(2704179) # numeric
#> [1] "2704179"
#> attr(,"class")
#> [1] "gbifid"
#> attr(,"match")
#> [1] "found"
#> attr(,"multiple_matches")
#> [1] FALSE
#> attr(,"pattern_match")
#> [1] FALSE
#> attr(,"uri")
#> [1] "http://www.gbif.org/species/2704179"
as.gbifid("2704179") # character
#> [1] "2704179"
#> attr(,"class")
#> [1] "gbifid"
#> attr(,"match")
#> [1] "found"
#> attr(,"multiple_matches")
#> [1] FALSE
#> attr(,"pattern_match")
#> [1] FALSE
#> attr(,"uri")
#> [1] "http://www.gbif.org/species/2704179"
as.gbifid(list("2704179","2435099","3171445")) # list, either numeric or character
#> [1] "2704179" "2435099" "3171445"
#> attr(,"class")
#> [1] "gbifid"
#> attr(,"match")
#> [1] "found" "found" "found"
#> attr(,"multiple_matches")
#> [1] FALSE FALSE FALSE
#> attr(,"pattern_match")
#> [1] FALSE FALSE FALSE
#> attr(,"uri")
#> [1] "http://www.gbif.org/species/2704179"
#> [2] "http://www.gbif.org/species/2435099"
#> [3] "http://www.gbif.org/species/3171445"
These as.*() functions do a quick check of the web resource to make sure it’s a real ID. However, you can turn this check off, making this coercion much faster:
system.time( replicate(3, as.gbifid(c("2704179","2435099","3171445"), check=TRUE)) )
#> user system elapsed
#> 0.081 0.002 1.776
system.time( replicate(3, as.gbifid(c("2704179","2435099","3171445"), check=FALSE)) )
#> user system elapsed
#> 0.004 0.000 0.003
What taxa are downstream of my taxon of interest?
If someone is not a taxonomic specialist on a particular taxon he likely does not know what children taxa are within a family, or within a genus. This task becomes especially unwieldy when there are a large number of taxa downstream. You can of course go to a website like Wikispecies or Encyclopedia of Life to get downstream names. However, taxize provides an easy way to programatically search for downstream taxa, both for the Catalogue of Life (CoL) and the Integrated Taxonomic Information System. Here is a short example using the CoL in which we want to find all the species within the genus Apis (honey bees).
downstream("Apis", downto = "Species", db = "col")
#> name rank colid
#> 1 Apis genus 015be25f6b061ba517f495394b80f108
#> 2 Actinomadura apis species 1182a102a18b40aa19385bf5f1f53367
#> 3 Anisocentropus apis species 8891d18874dde14e44df52e931c44206
#> 4 Apis andreniformis species 7a4a38c5095963949d6d6ec917d471de
#> 5 Apis cerana species 39610a4ceff7e5244e334a3fbc5e47e5
#> 6 Apis dorsata species e1d4cbf3872c6c310b7a1c17ddd00ebc
#> 7 Apis florea species 92dca82a063fedd1da94b3f3972d7b22
#> 8 Apis koschevnikovi species 4bbc06b9dfbde0b72c619810b564c6e6
#> 9 Apis mellifera species 67cbbcf92cd60748759e58e802d98518
#> 10 Apis nigrocincta species 213668a26ba6d2aad9575218f10d422f
#> name_status kingdom family acc_name
#> 1 accepted name Animalia Apidae <NA>
#> 2 accepted name Bacteria Thermomonosporaceae <NA>
#> 3 accepted name Animalia Calamoceratidae <NA>
#> 4 accepted name Animalia Apidae <NA>
#> 5 accepted name Animalia Apidae <NA>
#> 6 accepted name Animalia Apidae <NA>
#> 7 accepted name Animalia Apidae <NA>
#> 8 accepted name Animalia Apidae <NA>
#> 9 accepted name Animalia Apidae <NA>
#> 10 accepted name Animalia Apidae <NA>
...
#> $Apis
#> childtaxa_id childtaxa_name childtaxa_rank
#> 1 7a4a38c5095963949d6d6ec917d471de Apis andreniformis species
#> 2 39610a4ceff7e5244e334a3fbc5e47e5 Apis cerana species
#> 3 e1d4cbf3872c6c310b7a1c17ddd00ebc Apis dorsata species
#> 4 92dca82a063fedd1da94b3f3972d7b22 Apis florea species
#> 5 4bbc06b9dfbde0b72c619810b564c6e6 Apis koschevnikovi species
#> 6 67cbbcf92cd60748759e58e802d98518 Apis mellifera species
#> 7 213668a26ba6d2aad9575218f10d422f Apis nigrocincta species
#>
#> attr(,"class")
#> [1] "downstream"
#> attr(,"db")
#> [1] "col"
We can also request data from ITIS
downstream("Apis", downto = "Species", db = "itis")
#> tsn target
#> 1 592329 Acanthagrion latapistylum
#> 2 606339 Acritoptila capistra
#> 3 958884 Actinomadura apis
#> 4 633997 Aglaoapis
#> 5 756292 Aglaoapis alata
#> 6 756293 Aglaoapis brevipennis
#> 7 756294 Aglaoapis tridentata
#> 8 166914 Amblyapistus
#> 9 166915 Amblyapistus binotata
#> 10 166916 Amblyapistus macracanthus
#> commonNames
#> 1 NA
#> 2 NA
#> 3 NA
#> 4 NA
#> 5 NA
#> 6 NA
#> 7 NA
#> 8 NA
#> 9 redskin fish
#> 10 cockscomb fish
#> nameUsage
#> 1 valid
#> 2 valid
#> 3 valid
#> 4 valid
#> 5 valid
#> 6 valid
#> 7 valid
#> 8 invalid
#> 9 invalid
#> 10 invalid
#> $Apis
#> tsn parentname parenttsn taxonname rankid rankname
#> 1 No data No data No data No data No data no data
#>
#> attr(,"class")
#> [1] "downstream"
#> attr(,"db")
#> [1] "itis"
Direct children
You may sometimes only want the direct children. We got you covered on that front, with methods for ITIS, NCBI, and Catalogue of Life. For example, let’s get direct children (species in this case) of the bee genus Apis using COL data:
children(get_colid("Apis"))
#> name rank colid
#> 1 Apis genus 015be25f6b061ba517f495394b80f108
#> 2 Actinomadura apis species 1182a102a18b40aa19385bf5f1f53367
#> 3 Anisocentropus apis species 8891d18874dde14e44df52e931c44206
#> 4 Apis andreniformis species 7a4a38c5095963949d6d6ec917d471de
#> 5 Apis cerana species 39610a4ceff7e5244e334a3fbc5e47e5
#> 6 Apis dorsata species e1d4cbf3872c6c310b7a1c17ddd00ebc
#> 7 Apis florea species 92dca82a063fedd1da94b3f3972d7b22
#> 8 Apis koschevnikovi species 4bbc06b9dfbde0b72c619810b564c6e6
#> 9 Apis mellifera species 67cbbcf92cd60748759e58e802d98518
#> 10 Apis nigrocincta species 213668a26ba6d2aad9575218f10d422f
#> 11 Ascosphaera apis species 088549f2fb602367e84d5ffdb8c1d4fc
#> 12 Candida apis species 3219a9635d3438e8b76a645cecf87287
#> 13 Eristalis apis species 16d7c8023308d38f6bb831ed5fa82002
#> 14 Hister apis species d2d7483acf488b5ed932f49b0aa51d19
#> 15 Ifephylus apis species 9b4d00e009b58bbfc003b51bd3d0c6f0
#> 16 Impatiens nidus-apis species 6aecf448e6aa0cb46387066db94426d1
#> 17 Kirkaldykra apis species 70a68f13454abd937aabf56746f4a6ad
#> 18 Mallota apis species 10c3c3921d2ea9f9425ef9fd41914520
#> 19 Melanosella mors-apis species 4ac238f1597847dbc7998d97b8d45a0e
#> 20 Microdon apis species 9be92242562eb923e711dc24b7bbab9a
#> 21 Nosema apis species 5b2838dfd0ec15844fc6f659f7580322
#> 22 Scutirodes apis species 164ab3ac910547bc945cdbb994be1ee5
#> 23 Spiroplasma apis species 789f91571ce55de4df9821f2d05efab0
#> 24 Trichomonascus apis species 17dc4d840323e2c5b87e67a952f6dff3
#> 25 Pericystis apis species 088549f2fb602367e84d5ffdb8c1d4fc
#> 26 Pericystis apis species 088549f2fb602367e84d5ffdb8c1d4fc
#> 27 Torulopsis apis species 3219a9635d3438e8b76a645cecf87287
#> 28 Torulopsis apis species 3219a9635d3438e8b76a645cecf87287
#> 29 Apis aestuans species a517bc572c3c2697fe3bbfabc46a1493
#> 30 Apis alpina species f2781627115e4212ddab5979cdd425d2
#> 31 Apis bicornis species e67e82d00faae69da173bb31f9914056
#> 32 Apis canescens species d6b8850db971d65d6079e3a22f35e10e
#> 33 Apis clypeata species 706060924801130f6c3abf454087c100
#> 34 Apis cunicularia species ebc3c5166ce2cabf419c4c6dc332cf3b
#> 35 Apis etrusca species 6d27fd39a1d8b10050ba4e331987f3c9
#> 36 Apis globosa species 254c8e847ca4ff128bba57fe94deb98d
#> 37 Apis hispanica species e8d2057a3efeb2cfdaebe27ea8191cd5
#> 38 Apis hypnorum species dfb743f54f50b9b9dbee378473542821
#> 39 Apis ichneumonea species 13c35287e20ab9373fa445dbc44981ea
#> 40 Apis lapidaria species f8da5667af3562ebc0f6a83e1ec408f0
#> 41 Apis muscorum species 5bbfe59da5ce7fe59eb9ca3a7a45916c
#> 42 Apis mystacea species fba8e4752a7fa5939a7eae293ba633ec
#> 43 Apis obsoleta species da42bcb6cc0267903fb175f8a215aecb
#> 44 Apis rostrata species e155a4277b66d1114182cafd875afbe3
#> 45 Apis rostrata species e155a4277b66d1114182cafd875afbe3
#> 46 Apis rufa species e67e82d00faae69da173bb31f9914056
#> 47 Apis signata species 551f101ad3b9bc17b24575585b2500c1
#> 48 Apis smaragdula species 4bc5c886b061e17e9aecb537a04c616d
#> 49 Apis spinulosa species 56e7e9f854c9ed31ea6d0a06567607d0
#> 50 Apis subterranea species 3d2adff364a87bf7dd30524aa8071807
#> name_status kingdom family acc_name
#> 1 accepted name Animalia Apidae <NA>
#> 2 accepted name Bacteria Thermomonosporaceae <NA>
#> 3 accepted name Animalia Calamoceratidae <NA>
#> 4 accepted name Animalia Apidae <NA>
#> 5 accepted name Animalia Apidae <NA>
#> 6 accepted name Animalia Apidae <NA>
#> 7 accepted name Animalia Apidae <NA>
#> 8 accepted name Animalia Apidae <NA>
#> 9 accepted name Animalia Apidae <NA>
#> 10 accepted name Animalia Apidae <NA>
#> 11 accepted name Fungi Ascosphaeraceae <NA>
#> 12 accepted name Fungi Not assigned <NA>
#> 13 accepted name Animalia Syrphidae <NA>
#> 14 accepted name Animalia Histeridae <NA>
#> 15 accepted name Animalia Miridae <NA>
#> 16 accepted name Plantae Balsaminaceae <NA>
#> 17 accepted name Animalia Cicadellidae <NA>
#> 18 accepted name Animalia Syrphidae <NA>
#> 19 accepted name Fungi Not assigned <NA>
#> 20 accepted name Animalia Syrphidae <NA>
#> 21 accepted name Protozoa Nosematidae <NA>
#> 22 accepted name Animalia Noctuidae <NA>
#> 23 accepted name Bacteria Spiroplasmataceae <NA>
#> 24 accepted name Fungi Trichomonascaceae <NA>
#> 25 ambiguous synonym <NA> <NA> Ascosphaera apis
#> 26 ambiguous synonym <NA> <NA> Ascosphaera apis
#> 27 ambiguous synonym <NA> <NA> Candida apis
#> 28 ambiguous synonym <NA> <NA> Candida apis
#> 29 synonym <NA> <NA> Xylocopa aestuans
#> 30 synonym <NA> <NA> Bombus alpinus
#> 31 synonym <NA> <NA> Osmia rufa
#> 32 synonym <NA> <NA> Bembix canescens
#> 33 synonym <NA> <NA> Lestica clypeata
#> 34 synonym <NA> <NA> Colletes cunicularius
#> 35 synonym <NA> <NA> Tachytes etruscus
#> 36 synonym <NA> <NA> Exomalopsis similis
#> 37 synonym <NA> <NA> Tachytes freygessneri
#> 38 synonym <NA> <NA> Bombus hypnorum
#> 39 synonym <NA> <NA> Sphex ichneumoneus
#> 40 synonym <NA> <NA> Bombus lapidarius
#> 41 synonym <NA> <NA> Bombus muscorum
#> 42 synonym <NA> <NA> Argogorytes mystaceus
#> 43 synonym <NA> <NA> Tachytes obsoletus
#> 44 synonym <NA> <NA> Bembix rostrata
#> 45 synonym <NA> <NA> Bembix rostrata
#> 46 synonym <NA> <NA> Osmia rufa
#> 47 synonym <NA> <NA> Stictia signata
#> 48 synonym <NA> <NA> Ceratina smaragdula
#> 49 synonym <NA> <NA> Hoplosmia spinulosa
#> 50 synonym <NA> <NA> Bombus subterraneus
#> $`015be25f6b061ba517f495394b80f108`
#> childtaxa_id childtaxa_name childtaxa_rank
#> 1 7a4a38c5095963949d6d6ec917d471de Apis andreniformis species
#> 2 39610a4ceff7e5244e334a3fbc5e47e5 Apis cerana species
#> 3 e1d4cbf3872c6c310b7a1c17ddd00ebc Apis dorsata species
#> 4 92dca82a063fedd1da94b3f3972d7b22 Apis florea species
#> 5 4bbc06b9dfbde0b72c619810b564c6e6 Apis koschevnikovi species
#> 6 67cbbcf92cd60748759e58e802d98518 Apis mellifera species
#> 7 213668a26ba6d2aad9575218f10d422f Apis nigrocincta species
#>
#> attr(,"class")
#> [1] "children"
#> attr(,"db")
#> [1] "col"
The direct children (genera in this case) of Pinaceae using NCBI data:
children("Pinaceae", db = "ncbi")
#> $Pinaceae
#> childtaxa_id childtaxa_name childtaxa_rank
#> 1 123600 Nothotsuga genus
#> 2 64685 Cathaya genus
#> 3 3358 Tsuga genus
#> 4 3356 Pseudotsuga genus
#> 5 3354 Pseudolarix genus
#> 6 3337 Pinus genus
#> 7 3328 Picea genus
#> 8 3325 Larix genus
#> 9 3323 Keteleeria genus
#> 10 3321 Cedrus genus
#> 11 3319 Abies genus
#>
#> attr(,"class")
#> [1] "children"
#> attr(,"db")
#> [1] "ncbi"
Get NCBI ID from GenBank Ids
With accession numbers
genbank2uid(id = 'AJ748748')
#> [1] "282199"
#> attr(,"class")
#> [1] "uid"
#> attr(,"match")
#> [1] "found"
#> attr(,"multiple_matches")
#> [1] FALSE
#> attr(,"pattern_match")
#> [1] FALSE
#> attr(,"uri")
#> [1] "http://www.ncbi.nlm.nih.gov/taxonomy/282199"
With gi numbers
genbank2uid(id = 62689767)
#> [1] "282199"
#> attr(,"class")
#> [1] "uid"
#> attr(,"match")
#> [1] "found"
#> attr(,"multiple_matches")
#> [1] FALSE
#> attr(,"pattern_match")
#> [1] FALSE
#> attr(,"uri")
#> [1] "http://www.ncbi.nlm.nih.gov/taxonomy/282199"
Citing
To cite taxize in publications use:
Scott Chamberlain and Eduard Szocs (2013). taxize - taxonomic search and retrieval in R. F1000Research, 2:191. URL: http://f1000research.com/articles/2-191/v2.
Scott Chamberlain, Eduard Szocs, Carl Boettiger, Karthik Ram, Ignasi Bartomeus, John Baumgartner, Zachary Foster, James O’Donnell, and Jari Oksanen (2017). taxize: Taxonomic information from around the web. R package version 0.9.0. https://github.com/ropensci/taxize
License and bugs
- License: MIT
- Report bugs at our Github repo for taxize
