bold
====
[![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)
[![cran version](https://www.r-pkg.org/badges/version/bold)](https://cran.r-project.org/package=bold)
[![cran checks](https://cranchecks.info/badges/worst/bold)](https://cranchecks.info/pkgs/bold)
[![R-check](https://github.com/ropensci/bold/workflows/R-check/badge.svg)](https://github.com/ropensci/bold/actions/)
[![codecov.io](https://codecov.io/github/ropensci/bold/coverage.svg?branch=master)](https://codecov.io/github/ropensci/bold?branch=master)
[![rstudio mirror downloads](https://cranlogs.r-pkg.org/badges/bold)](https://github.com/r-hub/cranlogs.app)
`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://v4.boldsystems.org/index.php/api_home
See also the taxize book for more options for taxonomic workflows with BOLD: https://taxize.dev/
## Installation
__Installation instructions__
__Stable Version__
```r
install.packages("bold")
```
__Development Version__
Install `sangerseqR` first (used in function `bold::bold_trace()` only)
For R < 3.5
```r
source("http://bioconductor.org/biocLite.R")
biocLite("sangerseqR")
```
For R >= 3.5
```r
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("sangerseqR")
```
Then install `bold`
```r
remotes::install_github("ropensci/bold")
```
## Usage
```r
library("bold")
```
### Search for sequence data only
Default is to get a list back
```r
bold_seq(taxon='Coelioxys')[[1]]
#> $id
#> [1] "ABEE117-17"
#>
#> $name
#> [1] "Coelioxys elongata"
#>
#> $gene
#> [1] "ABEE117-17"
#>
#> $sequence
#> [1] "------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------TTATCATTATATACATATCATCCTTCCCCATCAGTTGATTTAGCAATTTTTTYTTTACATTTATCAGGAATTTYTTYTATTATCGGATCAATAAATTTTATTGTAACAATTTTAATAATAAAAAATTATTCAATAAATTATAATCAAATACCTTTATTTCCATGATCAATTTTAATTACTACAATTTTATTATTATTATCATTACCTGTATTAGCAGGAGCTATTACAATATTATTATTTGATCGTAATTTAAATTCATCATTTTTTGACCCAATAGGAGGAGGAGATCCTATTTTATATCAACATTTATTTTG------------------------------------"
```
You can optionally get back the `crul` response object
```r
res <- bold_seq(taxon='Coelioxys', response=TRUE)
res$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"
#>
#> $`x-xss-protection`
#> [1] "1; mode=block"
```
### Search for specimen data only
By default you download `tsv` format data, which is given back to you as a `data.frame`
```r
res <- bold_specimens(taxon='Osmia')
head(res[,1:8])
#> processid sampleid recordID catalognum fieldnum
#> 1 BEECA373-06 05-NT-0373 514740 05-NT-0373
#> 2 BEECA607-06 05-NT-0607 516959 05-NT-0607
#> 3 BEECA963-07 01-OR-0790 554153 01-OR-0790
#> 4 BEECB358-07 04-WA-1076 596920 BBSL697174 04-WA-1076
#> 5 BEECB438-07 00-UT-1157 597000 BBSL432653 00-UT-1157
#> 6 BEECC1176-09 02-UT-2849 1060879 BBSL442586 02-UT-2849
#> institution_storing collection_code bin_uri
#> 1 York University, Packer Collection NA BOLD:AAI2013
#> 2 York University, Packer Collection NA BOLD:AAC8510
#> 3 York University, Packer Collection NA BOLD:ABZ3184
#> 4 Utah State University, Logan Bee Lab NA BOLD:AAC5797
#> 5 Utah State University, Logan Bee Lab NA BOLD:AAF2159
#> 6 York University, Packer Collection NA BOLD:AAE5368
```
### Search for specimen plus sequence data
By default you download `tsv` format data, which is given back to you as a `data.frame`
```r
res <- bold_seqspec(taxon='Osmia', sepfasta=TRUE)
res$fasta[1:2]
#> $`BEECA373-06`
#> [1] "-ATTTTATATATAATTTTTGCTATATGATCAGGTATAATCGGATCAGCAATAAGAATTATTATTCGTATAGAATTAAGAATTCCTGGTTCATGAATTTCAAATGATCAAACTTATAACTCTTTAGTAACTGCTCATGCTTTTTTAATAATTTTTTTCTTAGTTATACCTTTTTTAATTGGAGGATTTGGAAATTGATTAATTCCTTTAATATTAGGAATCCCGGATATAGCTTTCCCTCGAATAAATAATATTAGATTTTGACTTTTACCCCCTTCATTAATATTATTACTTTTAAGAAATTTTATAAATCCAAGACCAGGTACTGGATGAACTGTTTATCCTCCTCTTTCTTCTCATTTATTTCATTCTTCTCCTTCAGTTGATATAGCCATTTTTTCTTTACATATTTCCGGTTTATCTTCTATTATAGGTTCGTTAAATTTTATTGTTACAATTATTATAATAAAAAATATTTCTTTAAAACATATCCAATTACCTTTATTTCCATGATCTGTTTTTATTACTACTATCTTATTACTTTTTTCTTTACCTGTTTTAGCAGGAGCTATTACTATATTATTATTTGATCGAAATTTTAATACTTCATTTTTTGATCCTACAGGAGGTGGAGATCCAATCCTTTATCAACATTTATTT"
#>
#> $`BEECA607-06`
#> [1] "AATATTATATATAATTTTTGCTTTGTGATCTGGAATAATTGGTTCATCTATAAGAATTATTATTCGTATAGAATTAAGAATTCCTGGTTCATGAATTTCAAATGATCAAGTTTATAATTCATTAGTTACAGCTCATGCTTTTTTAATAATTTTTTTTTTAGTTATACCATTTATAATTGGAGGATTTGGAAATTGATTAGTTCCTTTAATATTAGGAATTCCTGATATAGCTTTTCCTCGAATAAATAATATTAGATTTTGATTATTACCACCATCATTAATACTTTTACTTTTAAGAAATTTTTTTAATCCAAGTTCAGGAACTGGATGAACTGTATATCCTCCTCTTTCATCATATTTATTTCATTCTTCACCTTCTGTTGATTTAGCTATTTTTTCTCTTCATATATCAGGTTTATCTTCTATTATAGGTTCATTAAACTTTATTGTAACTATTATTATAATAAAAAATATTTCTTTAAAGTATATTCAATTGCCATTATTTCCATGATCTGTTTTTATTACTACAATTCTTTTATTATTATCATTACCAGTTTTAGCAGGTGCTATTACTATATTATTATTTGATCGAAATTTTAATACTTCATTTTTTGATCCTACAGGAGGGGGAG--------------------------"
```
Or you can index to a specific sequence like
```r
res$fasta['GBAH0293-06']
#> $`GBAH0293-06`
#> [1] "------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------TTAATGTTAGGGATTCCAGATATAGCTTTTCCACGAATAAATAATATTAGATTTTGACTGTTACCTCCATCTTTAATATTATTACTTTTAAGAAATTTTTTAAATCCAAGTCCTGGAACAGGATGAACAGTTTATCCTCCTTTATCATCAAATTTATTTCATTCTTCTCCTTCAGTTGATTTAGCAATTTTTTCTTTACATATTTCAGGTTTATCTTCTATTATAGGTTCATTAAATTTTATTGTTACAATTATTATAATAAAAAATATTTCTTTAAAATATATTCAATTACCTTTATTTTCTTGATCTGTATTTATTACTACTATTCTTTTATTATTTTCTTTACCTGTATTAGCTGGAGCTATTACTATATTATTATTTGATCGAAATTTTAATACATCTTTTTTTGATCCAACAGGAGGGGGAGATCCAATTCTTTATCAACATTTATTTTGATTTTTTGGTCATCCTGAAGTTTATATTTTAATTTTACCTGGATTTGGATTAATTTCTCAAATTATTTCTAATGAAAGAGGAAAAAAAGAAACTTTTGGAAATATTGGTATAATTTATGCTATATTAAGAATTGGACTTTTAGGTTTTATTGTT---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------"
```
### Get trace files
This function downloads files to your machine - it does not load them into your R session - but prints out where the files are for your information.
```r
x <- bold_trace(ids = 'ACRJP618-11', progress = FALSE)
read_trace(x$ab1)
#> Number of datapoints: 8877
#> Number of basecalls: 685
#>
#> Primary Basecalls: NNNNNNNNNNNNNNNNNNGNNNTTGAGCAGGNATAGTAGGANCTTCTCTTAGTCTTATTATTCGAACAGAATTAGGAAATCCAGGATTTTTAATTGGAGATGATCAAATCTACAATACTATTGTTACGGCTCATGCTTTTATTATAATTTTTTTTATAGTTATACCTATTATAATTGGAGGATTTGGTAATTGATTAGTTCCCCTTATACTAGGAGCCCCAGATATAGCTTTCCCTCGAATAAACAATATAAGTTTTTGGCTTCTTCCCCCTTCACTATTACTTTTAATTTCCAGAAGAATTGTTGAAAATGGAGCTGGAACTGGATGAACAGTTTATCCCCCACTGTCATCTAATATTGCCCATAGAGGTACATCAGTAGATTTAGCTATTTTTTCTTTACATTTAGCAGGTATTTCCTCTATTTTAGGAGCGATTAATTTTATTACTACAATTATTAATATACGAATTAACAGTATAAATTATGATCAAATACCACTATTTGTGTGATCAGTAGGAATTACTGCTTTACTCTTATTACTTTCTCTTCCAGTATTAGCAGGTGCTATCACTATATTATTAACGGATCGAAATTTAAATACATCATTTTTTGATCCTGCAGGAGGAGGAGATCCAATTTTATATCAACATTTATTTTGATTTTTTGGACNTCNNNNAAGTTTAAN
#>
#> Secondary Basecalls:
```
### Large data
Sometimes with `bold_seq()` 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 attempts to give you back sequences
for all records under _Arthropoda_. This, as you can imagine, is a lot of
sequences.
```r
library("taxize")
```
Using `taxize::downstream` get children of _Arthropoda_
```r
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
```r
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.
```r
out <- lapply(nms, bold_seq)
```
## Citation
Get citation information for `bold` in R by running: `citation(package = 'bold')`
## Meta
* Please [report any issues or bugs](https://github.com/ropensci/bold/issues)
* License: MIT
* Get citation information for `bold` in R doing `citation(package = 'bold')`
* Please note that this project is released with a [Contributor Code of Conduct](https://ropensci.org/code-of-conduct/). By participating in this project you agree to abide by its terms.