rif

R client for the Neuroscience Information Framework APIs.

API docs at https://neuinfo.org/about/webservices

Auth

You now need an API key to use the NIF API. Steps:

Go to https://www.neuinfo.org/
If you don't have an account yet, register for an account.
Log in
Go to https://www.neuinfo.org/account/developer - you'll need to enter your password again
Create an API key
Store your API key ideally as an environment variable in .Renviron or similar. Or, you can save as an R option. (see ?Startup for help on env vars and R options). You can also pass in your API key to each function but that's not ideal.

Installation

CRAN version

install.packages("rif")

development version

install.packages("devtools")
devtools::install_github("ropensci/rif")

Load rif

library('rif')

Summary

out <- rif_summary("cellular")
head(out$result$federationSummary$results)

#>   parentCategory      category                   db      indexable
#> 1    Output Type Data or Model Barres Brain RNA-Seq ExpressionData
#> 2       Category    Expression Barres Brain RNA-Seq ExpressionData
#> 3       Category          Gene Barres Brain RNA-Seq ExpressionData
#> 4       Category          Cell Barres Brain RNA-Seq ExpressionData
#> 5       Category      Molecule        PubMed Health           Drug
#> 6    Output Type   Information        PubMed Health           Drug
#>          nifId count totalCount snippets
#> 1 scr_013736-2     9      22458     NULL
#> 2 scr_013736-2     9      22458     NULL
#> 3 scr_013736-2     9      22458     NULL
#> 4 scr_013736-2     9      22458     NULL
#> 5  nlx_32805-3     2      19179     NULL
#> 6  nlx_32805-3     2      19179     NULL
#>                                summaryString
#> 1 Barres Brain RNA-Seq: ExpressionData (9)[]
#> 2 Barres Brain RNA-Seq: ExpressionData (9)[]
#> 3 Barres Brain RNA-Seq: ExpressionData (9)[]
#> 4 Barres Brain RNA-Seq: ExpressionData (9)[]
#> 5                  PubMed Health: Drug (2)[]
#> 6                  PubMed Health: Drug (2)[]

Query

List NIF query categories

rif_query_categories()

#>  [1] "anatomy"             "antibody"            "catalognumber"      
#>  [4] "cell"                "coordinate"          "disease"            
#>  [7] "environment"         "fulltext"            "function"           
#> [10] "gene"                "genetargetreagent"   "genomiclocus"       
#> [13] "genomiclocusvariant" "genotype"            "identifier"         
#> [16] "interaction"         "interactiontype"     "moleculardomain"    
#> [19] "molecule"            "organism"            "pathway"            
#> [22] "phenotype"           "protocol"            "publication"        
#> [25] "quality"             "resource"            "sequence"           
#> [28] "sequencefeature"     "specimen"            "stage"              
#> [31] "strain"              "subcellularanatomy"

Vocabulary

Search for vocabulary terms

vocabulary_search("cell", limit = 3)

#>                                   uuid    term           id category
#> 1 c2aad6c6-a2b8-4818-b2c8-5271dd5f431c    cell NEMO_9559000     cell
#> 2 439b50ba-d1a6-4b4c-bbfd-d1d61d74ba69    cell   GO_0005623     cell
#> 3 8ddd9932-4e66-4a25-84af-237c0784cef4 On cell    nifext_32     Cell
#>   provider inferred acronym abbreviation synonyms definition
#> 1   NIFSTD    FALSE   FALSE        FALSE       NA         NA
#> 2   NIFSTD    FALSE   FALSE        FALSE       NA         NA
#> 3   NIFSTD    FALSE   FALSE        FALSE       NA         NA

Lexical

Break up text into various things

text <- "Lorem ipsum inceptos dolor nisi torquent porttitor donec, blandit scelerisque
mattis cras quis mi, aliquam sagittis. Convallis placerat commodo imperdiet varius nunc
tempus urna vitae ultrices tristique eu mi ornare velit donec, posuere laoreet pretium
vitae porta augue porta feugiat in sapien egestas. Quam odio nullam pulvinar litora
curabitur amet lacus sociosqu gravida ligula molestie dui netus fusce bibendum
scelerisque, dictum malesuada proin elit etiam aliquam, mattis euismod donec nisl facilisis."
text <- gsub("\n", "", text)

Sentences

lexical_sentences(text)

#> $sentence
#> [1] "Lorem ipsum inceptos dolor nisi torquent porttitor donec, blandit scelerisquemattis cras quis mi, aliquam sagittis."                                                                                       
#> [2] "Convallis placerat commodo imperdiet varius nunctempus urna vitae ultrices tristique eu mi ornare velit donec, posuere laoreet pretiumvitae porta augue porta feugiat in sapien egestas."                  
#> [3] "Quam odio nullam pulvinar litoracurabitur amet lacus sociosqu gravida ligula molestie dui netus fusce bibendumscelerisque, dictum malesuada proin elit etiam aliquam, mattis euismod donec nisl facilisis."

Chunks

head(lexical_chunks(text))

#>                                 token start end
#> 1                Lorem ipsum inceptos     0  20
#> 2 dolor nisi torquent porttitor donec    21  56
#> 3           blandit scelerisquemattis    58  83
#> 4                                cras    84  88
#> 5                             quis mi    89  96
#> 6                    aliquam sagittis    98 114

Entities

head(lexical_entities(text))

#>                        token start end
#> 1 Lorem ipsum inceptos dolor     0  26
#> 2   torquent porttitor donec    32  56
#> 3  blandit scelerisquemattis    58  83
#> 4                       cras    84  88
#> 5                    quis mi    89  96
#> 6         aliquam sagittis .    98 115

Literature

library("dplyr")
out <- literature_search(query = "cellular", count = 5)
out$result$publications %>%
  select(pmid, journal, year)

#> # A tibble: 5 x 3
#>       pmid
#> *    <chr>
#> 1 12944235
#> 2 27417120
#> 3  8789268
#> 4  2987169
#> 5 15088773
#> # ... with 2 more variables: journal <chr>, year <int>

Get retractions

out <- literature_retractions()
out[1:20]

#>  [1] "12768027" "11167165" "22576713" "17973093" "10050223" "21613570"
#>  [7] "12438313" "22364277" "26214776" "10784445" "17519423" "21177250"
#> [13] "23745088" "26009721" "1824564"  "15260988" "20656892" "1400454" 
#> [19] "12200953" "22893106"

Then get info on some articles

arts <- literature_pmid(pmid = out[1:2])
lapply(arts, "[[", "title")

#> [[1]]
#> [1] "Basic residues of the helix six domain of influenza virus M1 involved in nuclear translocation of M1 can be replaced by PTAP and YPDL late assembly domain motifs."
#> 
#> [[2]]
#> [1] "Point-of-care (POC) testing of lactate in the intensive care patient. Accuracy, reliability, and costs of different measurement systems."

Data

Search for data

out <- federation_search("cellular")
out$query

#> $clauses
#>   category property    query expansion id quoted require forbid
#> 1       NA       NA cellular      NULL NA  FALSE   FALSE  FALSE
#> 
#> $operator
#> [1] "AND"

head(out$result$results)

#>   parentCategory      category                   db      indexable
#> 1       Category    Expression Barres Brain RNA-Seq ExpressionData
#> 2       Category          Gene Barres Brain RNA-Seq ExpressionData
#> 3       Category          Cell Barres Brain RNA-Seq ExpressionData
#> 4    Output Type Data or Model Barres Brain RNA-Seq ExpressionData
#> 5       Category      Molecule        PubMed Health           Drug
#> 6    Output Type   Information        PubMed Health           Drug
#>          nifId count totalCount snippets
#> 1 scr_013736-2     9      22458     NULL
#> 2 scr_013736-2     9      22458     NULL
#> 3 scr_013736-2     9      22458     NULL
#> 4 scr_013736-2     9      22458     NULL
#> 5  nlx_32805-3     2      19179     NULL
#> 6  nlx_32805-3     2      19179     NULL
#>                                summaryString
#> 1 Barres Brain RNA-Seq: ExpressionData (9)[]
#> 2 Barres Brain RNA-Seq: ExpressionData (9)[]
#> 3 Barres Brain RNA-Seq: ExpressionData (9)[]
#> 4 Barres Brain RNA-Seq: ExpressionData (9)[]
#> 5                  PubMed Health: Drug (2)[]
#> 6                  PubMed Health: Drug (2)[]

Get some data

out <- federation_data(id = "nlx_152871-2")
out$result$result

#> # A tibble: 20 x 12
#>                                                   Gene
#>                                                  <chr>
#>  1                                tyrosine hydroxylase
#>  2                              maternally expressed 3
#>  3                       G protein-coupled receptor 37
#>  4                               TANK-binding kinase 1
#>  5                 zinc finger, ZZ domain containing 3
#>  6                         deleted in azoospermia-like
#>  7                                     forkhead box A2
#>  8                         phospholipase A2, group IIF
#>  9                                         homeobox C5
#> 10                              GATA binding protein 4
#> 11                             sal-like 4 (Drosophila)
#> 12                   nitric oxide synthase 1, neuronal
#> 13                          RIKEN cDNA C130073F10 gene
#> 14                           choline acetyltransferase
#> 15                                         cystatin 12
#> 16 ash1 (absent, small, or homeotic)-like (Drosophila)
#> 17                        neurogenic differentiation 4
#> 18                         developing brain homeobox 2
#> 19           zinc finger and SCAN domain containing 22
#> 20                                      Nanog homeobox
#> # ... with 11 more variables: Anatomical.Component <chr>,
#> #   Assay.Type <chr>, Theiler.Stage <chr>, Tissue <chr>,
#> #   Expression.Strength <chr>, Expression.Pattern <chr>,
#> #   Expression.Pattern.Location <chr>, Authors <chr>, Notes <chr>,
#> #   v_uuid <chr>, Source <chr>

rif