bold
accesses BOLD barcode data.
The Barcode of Life Data Systems (BOLD) is designed to support the generation and application of DNA barcode data. The platform consists of four main modules: a data portal, a database of barcode clusters, an educational portal, and a data collection workbench.
This package retrieves data from the BOLD database of barcode clusters, and allows for searching of over 1.7M public records using multiple search criteria including sequence data, specimen data, specimen plus sequence data, as well as trace files.
Documentation for the BOLD API: http:https://v4.boldsystems.org/index.php/api_home
See also the taxize book for more options for taxonomic workflows with BOLD: https://taxize.dev/
Installation instructions
Stable Version
install.packages("bold")
Development Version
Install sangerseqR
first if you're planning on downloading and reading trace files.
(The package is only used in the function bold::bold_read_trace()
)
For R < 3.5
source("http:https://bioconductor.org/biocLite.R")
biocLite("sangerseqR")
For R >= 3.5
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("sangerseqR")
Then install bold
remotes::install_github("ropensci/bold")
library("bold")
Default is to get a list back
bold_seq(taxon='Coelioxys')[[1]]
#> $id
#> [1] "ABEE117-17"
#>
#> $name
#> [1] "Coelioxys elongata"
#>
#> $gene
#> [1] "ABEE117-17"
#>
#> $sequence
#> [1] "------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------TTATCATTATATACATATCATCCTTCCCCATCAGTTGATTTAGCAATTTTTTYTTTACATTTATCAGGAATTTYTTYTATTATCGGATCAATAAATTTTATTGTAACAATTTTAATAATAAAAAATTATTCAATAAATTATAATCAAATACCTTTATTTCCATGATCAATTTTAATTACTACAATTTTATTATTATTATCATTACCTGTATTAGCAGGAGCTATTACAATATTATTATTTGATCGTAATTTAAATTCATCATTTTTTGACCCAATAGGAGGAGGAGATCCTATTTTATATCAACATTTATTTTG------------------------------------"
You can optionally get back the crul
response object
res <- bold_seq(taxon='Coelioxys', response=TRUE)
res$response_headers
#> $status
#> [1] "HTTP/2 200 "
#>
#> $server
#> [1] "nginx"
#>
#> $date
#> [1] "Mon, 20 Apr 2020 16:11:50 GMT"
#>
#> $`content-type`
#> [1] "application/x-download"
#>
#> $`x-powered-by`
#> [1] "PHP/5.3.15"
#>
#> $`content-disposition`
#> [1] "attachment; filename=fasta.fas"
#>
#> $`x-frame-options`
#> [1] "SAMEORIGIN"
#>
#> $`x-content-type-options`
#> [1] "nosniff"
#>
#> $`x-xss-protection`
#> [1] "1; mode=block"
By default you download tsv
format data, which is given back to you as a data.frame
.
res <- bold_specimens(taxon='Osmia')
head(res[,1:8])
#> processid sampleid recordID catalognum fieldnum
#> 1 BEECA373-06 05-NT-0373 514740 05-NT-0373
#> 2 BEECA607-06 05-NT-0607 516959 05-NT-0607
#> 3 BEECA963-07 01-OR-0790 554153 01-OR-0790
#> 4 BEECB358-07 04-WA-1076 596920 BBSL697174 04-WA-1076
#> 5 BEECB438-07 00-UT-1157 597000 BBSL432653 00-UT-1157
#> 6 BEECC1176-09 02-UT-2849 1060879 BBSL442586 02-UT-2849
#> institution_storing collection_code bin_uri
#> 1 York University, Packer Collection NA BOLD:AAI2013
#> 2 York University, Packer Collection NA BOLD:AAC8510
#> 3 York University, Packer Collection NA BOLD:ABZ3184
#> 4 Utah State University, Logan Bee Lab NA BOLD:AAC5797
#> 5 Utah State University, Logan Bee Lab NA BOLD:AAF2159
#> 6 York University, Packer Collection NA BOLD:AAE5368
By default you download tsv
format data, which is given back to you as a data.frame
.
You can get the sequences in a separated list with sepfasta=TRUE
.
res <- bold_seqspec(taxon='Osmia', sepfasta=TRUE)
res$fasta[1:2]
#> $`BEECA373-06`
#> [1] "-ATTTTATATATAATTTTTGCTATATGATCAGGTATAATCGGATCAGCAATAAGAATTATTATTCGTATAGAATTAAGAATTCCTGGTTCATGAATTTCAAATGATCAAACTTATAACTCTTTAGTAACTGCTCATGCTTTTTTAATAATTTTTTTCTTAGTTATACCTTTTTTAATTGGAGGATTTGGAAATTGATTAATTCCTTTAATATTAGGAATCCCGGATATAGCTTTCCCTCGAATAAATAATATTAGATTTTGACTTTTACCCCCTTCATTAATATTATTACTTTTAAGAAATTTTATAAATCCAAGACCAGGTACTGGATGAACTGTTTATCCTCCTCTTTCTTCTCATTTATTTCATTCTTCTCCTTCAGTTGATATAGCCATTTTTTCTTTACATATTTCCGGTTTATCTTCTATTATAGGTTCGTTAAATTTTATTGTTACAATTATTATAATAAAAAATATTTCTTTAAAACATATCCAATTACCTTTATTTCCATGATCTGTTTTTATTACTACTATCTTATTACTTTTTTCTTTACCTGTTTTAGCAGGAGCTATTACTATATTATTATTTGATCGAAATTTTAATACTTCATTTTTTGATCCTACAGGAGGTGGAGATCCAATCCTTTATCAACATTTATTT"
#>
#> $`BEECA607-06`
#> [1] "AATATTATATATAATTTTTGCTTTGTGATCTGGAATAATTGGTTCATCTATAAGAATTATTATTCGTATAGAATTAAGAATTCCTGGTTCATGAATTTCAAATGATCAAGTTTATAATTCATTAGTTACAGCTCATGCTTTTTTAATAATTTTTTTTTTAGTTATACCATTTATAATTGGAGGATTTGGAAATTGATTAGTTCCTTTAATATTAGGAATTCCTGATATAGCTTTTCCTCGAATAAATAATATTAGATTTTGATTATTACCACCATCATTAATACTTTTACTTTTAAGAAATTTTTTTAATCCAAGTTCAGGAACTGGATGAACTGTATATCCTCCTCTTTCATCATATTTATTTCATTCTTCACCTTCTGTTGATTTAGCTATTTTTTCTCTTCATATATCAGGTTTATCTTCTATTATAGGTTCATTAAACTTTATTGTAACTATTATTATAATAAAAAATATTTCTTTAAAGTATATTCAATTGCCATTATTTCCATGATCTGTTTTTATTACTACAATTCTTTTATTATTATCATTACCAGTTTTAGCAGGTGCTATTACTATATTATTATTTGATCGAAATTTTAATACTTCATTTTTTGATCCTACAGGAGGGGGAG--------------------------"
Or you can index to a specific sequence like
res$fasta['GBAH0293-06']
#> $`GBAH0293-06`
#> [1] "------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------TTAATGTTAGGGATTCCAGATATAGCTTTTCCACGAATAAATAATATTAGATTTTGACTGTTACCTCCATCTTTAATATTATTACTTTTAAGAAATTTTTTAAATCCAAGTCCTGGAACAGGATGAACAGTTTATCCTCCTTTATCATCAAATTTATTTCATTCTTCTCCTTCAGTTGATTTAGCAATTTTTTCTTTACATATTTCAGGTTTATCTTCTATTATAGGTTCATTAAATTTTATTGTTACAATTATTATAATAAAAAATATTTCTTTAAAATATATTCAATTACCTTTATTTTCTTGATCTGTATTTATTACTACTATTCTTTTATTATTTTCTTTACCTGTATTAGCTGGAGCTATTACTATATTATTATTTGATCGAAATTTTAATACATCTTTTTTTGATCCAACAGGAGGGGGAGATCCAATTCTTTATCAACATTTATTTTGATTTTTTGGTCATCCTGAAGTTTATATTTTAATTTTACCTGGATTTGGATTAATTTCTCAAATTATTTCTAATGAAAGAGGAAAAAAAGAAACTTTTGGAAATATTGGTATAATTTATGCTATATTAAGAATTGGACTTTTAGGTTTTATTGTT---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------"
Note: you can get several sequences for one process id. For example:
res <- bold_seqspec(taxon='Salix', sepfasta=TRUE)
res$fasta[names(res$fasta) == "SALIX204-08"]
#> $SALIX204-08
#> CCGCCCCTAA------ATTTACAAATTACCAAGATTCGAATTTATAACATTTACTATTCAATTTAACC-------------------TTTTTTTATAAGTCTTA-------------------------TAAGAAAGAAATACAAAAGTAAAAAAAAAA-TTATTTAAGGAGCAATGCCAACCCTCTTGATAGAACAAGAAATTGGCGATTGCTCCTTTTTTTTTTTT--CAAAAGCTCGTACACACTAAGACAAAAGTCTTATCCATTTACAAAAGTCTTATCCATTTGT
#> $SALIX204-08
#> [1] ATTGGAACGCCAAGTTGCTCTTGATTCGGGGGTTCCTGCTATAGCCGAACACGAGGGAAAGATAATTTATACCGACATTGACAAGATTATTTTATCGGGGAATGGTTATACTGTAAGCATTCCATTAGTTATGTATCAACGTTCCAACAAAAATACCTGTATGCATCAAAAAACTCAGGTTCAGCGAGGAAAATGCATTAAAAGGGGACAAGTTTTGGCGGACGGTGCCGCTACAGTTGGTGGCGAACTCGCCTTGGGCAAAAACATATTAGTAGCTTATATGCCATGGGAAGGCTACAATTTTGAAGATGCGGTACTCATTAGCGAACGTCTGGTATATGAAGATGTTTATACTTCT
#> $SALIX204-08
#> [1] TATTGGATTTGTTGCTAAAATATCGGTATTAAACCCGAAACTCCCGGCGGATGACCAGTGACCCAAGGAAACGAAAGAATCGGTTATATTTTTCATACGATCTCCTCTTATTATAGACAGACTAATTATCTATTTATTTTTTTTTTT---TTAT-TATTCATTTACCTATTTCTAAATAGTAACTAGAGTCAAAAATATATTCAATTTCTATTAA--------------------TTAGAAATTTATTTTTTGTTCAATTGTAAATTTCTAATTAAGAACAATACTTAGTAAAATTGGGTATCAGGTCTTGTGCCAATTGCAAAATATCTACTTTA--TTTTTTTTTGTTACAACACTTCCTTAAAAAAGT-TTGGATTGGACTAACGAAGAAAGGGGAAGGAAGAAAGTGAATCAGTATACTAATTCCTCATCCCCCAATCAATCCTTCCCGTTGGGTTATTGTCCCAAT-AAAAATAAAACGAAATAAATAATTGTAGGAGTAAAATCTTGATAGAATTCGAAAAAGCAAGTACAAGAAATAAT-AAAAAAAAAATACGTA----------TTTTTTTTTTATTTTATAGGATTAGATTAAACAAAT
#> $SALIX204-08
#> [1] CTGCTGTAAGTTTTCGATGAAATTTTGAATACTATCCTAGAATAATTAATAATTCATGAGTTATTCAAGAGAAAAAATTCTACTAATTGATAAGATCAGATA--------------------AGTCTTCTAGTTCTTTCTAGTTCTTTATAGTCTAGGCCCTTGATTCAAACATTGAAGTTATTGTATAAACGTGAAAAATCTGGATTACCTACCCCATCTCCTCATTCTGAACTTTTTTCCATTCTATT----------------AAAAAAAACCTATTCGGTTAGATCCACCCGAAATAT------GGAATTTTCGGTATAAAAGCAAATTTTTGGCACACAAGACTCGACTCTTATTACA--------------------AATGAATTTAGAAAAATGCTTTTCTATTTCGAAAAAGTTCTAGAAACCACTTCATTTCTTGGTGTCAAAATGGGATATATGGTATAAATATAGAGAATCTATTTTCTTTTTTTCCAAACAAAAAAAAAA----GATCTTGGAGATTGTCTA
#> $SALIX204-08
#> [1] TGAGACTATGCTTGGCAAACGGGTTGATTATTCGGGGCGTTCCGTTATTGTCGTAGGCCCCTCACTTTCATTACATCGATGTGGATTGCCTCGCGAAATTGCAATAGAGCTTTTCCAGACATTTGTAATTCGTGGTCTAATTAGGCAACATCTTGCTTCAAACATAGGAGTTGCTAAGAGTAAAATTCGGGAAAAAGAGCCAATTGTATGGGGAATACTTCAGGAGGTTATGCGAGGACATCCTATATTGCTAAATAGAGCGCCTACTCTGCATAGATTAGGCATACAGGCATTCCAACCCATTTTAGTGGAAGGACGTGCTATTTGTTTACATCCATTAGTTCGTAAGGGATTCAATGCAGATTTTGATGGGGATCAAATGGCTGTTCATGTACCTTTATCGTTGGAGGCTCAAGCGGAGGCTCGTTTACTTATGTTTTCTCATATGAATCTCT
#> $SALIX204-08
#> [1] CAAACAGAAACTAAAGCAAGTGTTGGATTCAAGGCTGGTGTTAAAGATTATAAATTGACTTATTATACTCCTGAATATGAAACCAAAGATACTGATATCTTGGCAGCATTCCGAGTAACTCCTCAACCTGGAGTTCCGCCCGAGGAAGCAGGGGCCGCGGTAGCTGCTGAATCTTCTACTGGTACATGGACAACTGTGTGGACCGACGGGCTTACCAGTCTTGATCGTTATAAGGGACGATGCTACGACATCGAGCCCGTTGCTGGAGAAGAAAATCAATATATTGCTTATGTAGCTTACCCCTTAGACCTTTTTGAAGAAGGTTCTGTTACTAACATGTTTACTTCCATTGTGGGTAATGTATTTGGGTTCAAAGCCCTACGCGCTCTACGTCTAGAGGATTTGCGAATTCCTACTGCTTATGTTAAAACTTTTCAAGGCCCACCTCATGGTATCCAAGTTGAGAGAGATAAATTGAATAAGTATGGTCGCCCCCTATTGGGCTGTACTATTAAACCTAAATTGGGGTTATCCGCTAAGAATTACGGTAGAGCAGTTTATGAATGTCTACGCGGTGGACTTGATTTTACCAAAGATGATGAGAACGTGAACTCCCAACCATTTATGCGTTGGA
#> $SALIX204-08
#> [1] TTTCCACATTTAAATTATGTGTCAAATGGACTAATACCCTACCCCATCCATCTAGAAAAATTGGTTCAAATCCTTCGCTATTGGGTGAAAGATCCCTCCTCTTTGCATTTATTACGACTCTTTCTTCACGAGTATTGGAATTTGAACAGTCGTATTATTCCAAAGAAATCTATTTCTTTTTTTGCAAAAAAGACTCCAAGATTCTTCTTGTTCTTATATAATTCTCATGTATATGAATACGAGTCCGTTTTCTTTTTTCTTTGTAATCAATCCTTTCATTTCCGATTAACATTTTCTCAGGTCTTTCTTGAGCGAATATATTTCTATGGAAAAATAGAACATTTTGTA---------GAAGTCTTTACTAAGGATTGGGGGGACAGCCTATGCTTGCTCAAGGATCCTTTCATACATTATCTTAGATATCAAGGAAAATCCATTTTTGTCTCAAAGGATACGCCTCTTCTGATGAAAAAATGGAAATATTACCTTGTCAATTTATGTCAATGTCATTTTGATGTGTGCTTTCAACCCCCCAGGATCCATATAAACCCATTTTCATTATACAAGCATTCTTTCGCCTTATTAGGTTATCTTTCAAGTTCAAGTGTACGACTAAACCTTTCAGTGGTACGGAGTCAAATGCTAGAAAATGCATTTCTAATAGATAATATTATGAATAAACTCGATACAACAGTTTCAATTATTCCTTTGATTGGATCATTAGCAAAACTGAAATTTTGTAACGCAGTAGGACATCCCATTAGTAAACCGGCCTGGGCCGATTTTTCGGATTCTGATATTATCGACCGATTTGTCCGTATATGCAGAAATCTTTCTCATTATTATAGCGGATCCTCAAGAAAAAAGAGTTTGTATCGAATAAAATATATAC
#> $SALIX204-08
#> [1] TGCAGAATCCCGTGAACCATCGAGTCTTTGAACGCAAGTTGCGCCCGAGGCCTCCTGGTCGAGGGCACGTCTGCCT---GGGTGTCACGCATCGTCGCCCCC-------ACTCCCCTCG-------------------------GCTCACGAGGGCGGGGGCGGATACTGGTCTCCCGCGCGCTCCCGCCCGTGGTTGGCCT-AAAATCGAGTCCT-CGGCGGCGGTTGCC----ACGACAAGCGGTGGTTG-----------------------AGAGACCCTCGGACACGGTCGTGCGCGTGCTTG---------------------TCGCCCCCGGGAC--------------CTCCCGGACCCCCGAGCATTGGCTTTC-----------AAG-------------GATGCTCTCGTTGCGACCCCAGGTCAGGCGGGACTACCCGCTGAGTTTAA
The reason being some process have different sequences for different markers.
res$data[names(res$fasta) == "SALIX204-08", "markercode"]
#>[1] "trnH-psbA" "rpoB" "atpF-atpH" "psbK-psbI" "rpoC1" "rbcLa" "matK" "ITS2"
This function downloads files to your machine - it does not load them into your R session - but prints out where the files are for your information.
traces1 <- bold_trace(ids = 'ACRJP618-11', progress = FALSE)
traces1
#><bold trace files>
#>
#>./bold_trace_files/ACRJP618-11[LepF1,LepR1]_F.ab1
traces2 <- bold::bold_trace(ids = 'SALIX204-08', progress = FALSE)
traces2
#> <bold trace files>
#>
#> ./bold_trace_files/ACRJP618-11[LepF1,LepR1]_F.ab1
#> ./bold_trace_files/SALIX204-08[MatK-1RKIM-f,MatK-3FKIM-r]_F.ab1
#> ./bold_trace_files/SALIX204-08[MatK-1RKIM-f,MatK-3FKIM-r]_R.ab1
#> ./bold_trace_files/SALIX204-08[rbcLa-F,rbcLa-R]_F.ab1
#> ./bold_trace_files/SALIX204-08[rbcLa-F,rbcLa-R]_R.ab1
Then to read the files, you can use bold::bold_read_trace()
with either the boldtrace object or a subset of the paths.
bold_read_trace(trace1)
#> $`ACRJP618-11[LepF1,LepR1]_F.ab1`
#> Number of datapoints: 8877
#> Number of basecalls: 685
#>
#> Primary Basecalls: NNNNNNNNNNNNNNNNNNGNNNTTGAGCAGGNATAGTAGGANCTTCTCTTAGTCTTATTATTCGAACAGAATTAGGAAATCCAGGATTTTTAATTGGAGATGATCAAATCTACAATACTATTGTTACGGCTCATGCTTTTATTATAATTTTTTTTATAGTTATACCTATTATAATTGGAGGATTTGGTAATTGATTAGTTCCCCTTATACTAGGAGCCCCAGATATAGCTTTCCCTCGAATAAACAATATAAGTTTTTGGCTTCTTCCCCCTTCACTATTACTTTTAATTTCCAGAAGAATTGTTGAAAATGGAGCTGGAACTGGATGAACAGTTTATCCCCCACTGTCATCTAATATTGCCCATAGAGGTACATCAGTAGATTTAGCTATTTTTTCTTTACATTTAGCAGGTATTTCCTCTATTTTAGGAGCGATTAATTTTATTACTACAATTATTAATATACGAATTAACAGTATAAATTATGATCAAATACCACTATTTGTGTGATCAGTAGGAATTACTGCTTTACTCTTATTACTTTCTCTTCCAGTATTAGCAGGTGCTATCACTATATTATTAACGGATCGAAATTTAAATACATCATTTTTTGATCCTGCAGGAGGAGGAGATCCAATTTTATATCAACATTTATTTTGATTTTTTGGACNTCNNNNAAGTTTAAN
#>
#> Secondary Basecalls:
bold_read_trace(trace2$ab1[1:2])
># $`ACRJP618-11[LepF1,LepR1]_F.ab1`
># Number of datapoints: 8877
># Number of basecalls: 685
>#
># Primary Basecalls: NNNNNNNNNNNNNNNNNNGNNNTTGAGCAGGNATAGTAGGANCTTCTCTTAGTCTTATTATTCGAACAGAATTAGGAAATCCAGGATTTTTAATTGGAGATGATCAAATCTACAATACTATTGTTACGGCTCATGCTTTTATTATAATTTTTTTTATAGTTATACCTATTATAATTGGAGGATTTGGTAATTGATTAGTTCCCCTTATACTAGGAGCCCCAGATATAGCTTTCCCTCGAATAAACAATATAAGTTTTTGGCTTCTTCCCCCTTCACTATTACTTTTAATTTCCAGAAGAATTGTTGAAAATGGAGCTGGAACTGGATGAACAGTTTATCCCCCACTGTCATCTAATATTGCCCATAGAGGTACATCAGTAGATTTAGCTATTTTTTCTTTACATTTAGCAGGTATTTCCTCTATTTTAGGAGCGATTAATTTTATTACTACAATTATTAATATACGAATTAACAGTATAAATTATGATCAAATACCACTATTTGTGTGATCAGTAGGAATTACTGCTTTACTCTTATTACTTTCTCTTCCAGTATTAGCAGGTGCTATCACTATATTATTAACGGATCGAAATTTAAATACATCATTTTTTGATCCTGCAGGAGGAGGAGATCCAATTTTATATCAACATTTATTTTGATTTTTTGGACNTCNNNNAAGTTTAAN
>#
># Secondary Basecalls:
>#
># $`SALIX204-08[MatK-1RKIM-f,MatK-3FKIM-r]_F.ab1`
># Number of datapoints: 16299
># Number of basecalls: 877
>#
># Primary Basecalls: NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNTACGACTCTTTCTTCACGAGTATTGGAATTTGAACAGTCGTATTATTCCAAAGAAATCTATTTCTTTTTTTGCAAAAAAGACTCCAAGATTCTTCTTGTTCTTATATAATTCTCATGTATATGAATACGAGTCCGTTTTCTTTTTTCTTTGTAATCAATCCTTTCATTTCCGATTAACATTTTCTCAGGTCTTTCTTGAGCGAATATATTTCTATGGAAAAATAGAACATTTTGTAGAAGTCTTTACTAAGGATTGGGGGGACAGCCTATGCTTGCTCAAGGATCCTTTCATACATTATCTTAGATATCAAGGAAAATCCATTTTTGTCTCAAAGGATACGCCTCTTCTGATGAAAAAATGGAAATATTACCTTGTCAATTTATGTCAATGTCATTTTGATGTGTGCTTTCAACCCCCCAGGATCCATATAAACCCATTTTCATTATACAAGCATTCNTTCGCCTTATTAGGTTATCTTTCNAGTTCNAGTGNNCNACTNANCCTTTCAGTGGTACGGAGTCAAATGCTANAAAATGCATTTCTAATANATAATATTATGAATAAACTCGATACAACAGTTTCAATTANTCCTTTGATTGGATCATTAGCANAACTGAAATTTTGTNACGCNGTANGACATCCCATTAGTNAAACNGGCCTGNGCCGATTTTTCGGATTCTGATATTANCNACNGANTTGTCCNTNNNNNCAGAAATCNNNNTCATTNTNANNNCNGATCCNNNAGAAANANGAANTNNTATCNAATANAATATANNNTTCNNCTTTCNTGNGNNANNNCTTNGGCTCNTNANCNNNNANTNNNNAANNGN
>#
># Secondary Basecalls:
Sometimes with bold_seq()
, bold_seqspec()
and bold_specimen()
you request a lot of data, which can cause problems due
to BOLD's servers.
An example is the taxonomic name Arthropoda. When you send a request like
bold_seq(taxon = "Arthropoda")
, bold_seqspec(taxon = "Arthropoda")
or bold_specimen(taxon = "Arthropoda")
BOLD attempts to give you back sequences and/or specimen information for all records under Arthropoda. This, as you can imagine, is a lot of sequences.
library("taxize")
Using taxize::downstream
get children of Arthropoda
x <- downstream("Arthropoda", db = "ncbi", downto = "class")
#> ══ 1 queries ═══════════════
#> ✔ Found: Arthropoda
#> ══ Results ═════════════════
#>
#> ● Total: 1
#> ● Found: 1
#> ● Not Found: 0
nms <- x$Arthropoda$childtaxa_name
Optionally, check that the name exists in BOLD's data. Any that are not in BOLD will give back a row of NAs
checks <- bold_tax_name(nms)
# all is good
checks[,1:5]
#> taxid taxon tax_rank tax_division parentid
#> 1 26059 Pycnogonida class Animalia 20
#> 2 63 Arachnida class Animalia 20
#> 3 74 Merostomata class Animalia 20
#> 4 493944 Pauropoda class Animalia 20
#> 5 80390 Symphyla class Animalia 20
#> 6 85 Diplopoda class Animalia 20
#> 7 75 Chilopoda class Animalia 20
#> 8 82 Insecta class Animalia 20
#> 9 372 Collembola class Animalia 20
#> 10 734357 Protura class Animalia 20
#> 11 84 Remipedia class Animalia 20
#> 12 73 Cephalocarida class Animalia 20
#> 13 68 Branchiopoda class Animalia 20
#> 14 765970 Hexanauplia class Animalia 20
#> 15 69 Malacostraca class Animalia 20
#> 16 889450 Ichthyostraca class Animalia 20
#> 17 NA <NA> <NA> <NA> NA
#> 18 80 Ostracoda class Animalia 20
Then pass those names to bold_seq()
. You could pass all names in at once,
but we're trying to avoid the large data request problem here, so run each
one separately with lapply
or a for loop like request.
out <- lapply(nms, bold_seq)
Get citation information for bold
in R by running: citation(package = 'bold')
- Please report any issues or bugs
- License: MIT
- Get citation information for
bold
in R doingcitation(package = 'bold')
- Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.