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DataSpaceR is an R interface tothe CAVDDataSpace, a data sharing and discoverytool that facilitates exploration of HIV immunological data frompre-clinical and clinical HIV vaccine studies.

This package is intended for use by immunologists, bioinformaticians, andstatisticians in HIV vaccine research, or anyone interested in theanalysis of HIV immunological data across assays, studies, and time.

This package simplifies access to the database by taking advantage ofthe standardization of the database to hide all theRlabkey specific code awayfrom the user, and it allows the users to access the study-specificdatasets viaan object-orientedparadigm.

For more detailed examples and detailed documentation, seetheintroductoryvignetteandthe pkgdown site.

For a quick guide of how to use the API, see ourcheat sheet .

Install from CRAN:

install.packages("DataSpaceR")

You can install the latest development version fromGitHub withdevtools:

# install.packages("devtools")devtools::install_github("ropensci/DataSpaceR")

The database is accessed with the user’s credentials. A netrc filestoring login and password information isrequired.

1. Create an account and read the termsof use
2. On your R console, create a netrc file using a function fromDataSpaceR:

library(DataSpaceR)writeNetrc(login="yourEmail@address.com",password="yourSecretPassword",netrcFile="/your/home/directory/.netrc"# use getNetrcPath() to get the default path)

This will create a netrc file in your home directory.

Alternatively, you can manually create a netrc file in thecomputer running R.

• On Windows, this file should be named_netrc
• On UNIX, it should be named.netrc
• The file should be located in the user’s home directory, and thepermissions on the file should be unreadable for everybody exceptthe owner
• To determine home directory, runSys.getenv("HOME") in R

The following three lines must be included in the.netrc or_netrcfile either separated by white space (spaces, tabs, or newlines) orcommas. Multiple such blocks can exist in one file.

machine dataspace.cavd.orglogin myuser@domain.compassword supersecretpassword

Seeherefor more information aboutnetrc.

The general idea is that the user:

1. creates an instance ofDataSpaceConnection class viaconnectDS
2. browses available studies and groups in the instance viaavailableStudies andavailableGroups
3. creates a connection to a specific study viagetStudy or a groupviagetGroup
4. retrieves datasets by name viagetDataset

library(DataSpaceR)#> By exporting data from the CAVD DataSpace, you agree to be bound by the Terms of Use available on the CAVD DataSpace sign-in page at https://dataspace.cavd.orgcon<- connectDS()con#> <DataSpaceConnection>#>   URL: https://dataspace.cavd.org#>   User: jkim2345@scharp.org#>   Available studies: 273#>     - 77 studies with data#>     - 5049 subjects#>     - 423195 data points#>   Available groups: 6#>   Available publications: 1530#>     - 12 publications with data

connectDS() will create a connection to DataSpace.

knitr::kable(head(con$availableStudies))

knitr::kable(con$availableGroups)

Note: A group is a curated collection of participants fromfiltering of treatments, products, studies, or species, and it iscreated inthe DataSpaceApp.

Check outthe referencepageofDataSpaceConnection for all available fields and methods.

cvd408<-con$getStudy("cvd408")cvd408#> <DataSpaceStudy>#>   Study: cvd408#>   URL: https://dataspace.cavd.org/CAVD/cvd408#>   Available datasets:#>     - Binding Ab multiplex assay#>     - Demographics#>     - Intracellular Cytokine Staining#>     - Neutralizing antibody#>   Available non-integrated datasets:class(cvd408)#> [1] "DataSpaceStudy" "R6"

knitr::kable(cvd408$availableDatasets)

which will print names of available datasets.

NAb<-cvd408$getDataset("NAb")dim(NAb)#> [1] 540  33colnames(NAb)#>  [1] "participant_id"      "participant_visit"   "visit_day"#>  [4] "assay_identifier"    "summary_level"       "specimen_type"#>  [7] "antigen"             "antigen_type"        "virus"#> [10] "virus_type"          "virus_insert_name"   "clade"#> [13] "neutralization_tier" "tier_clade_virus"    "target_cell"#> [16] "initial_dilution"    "titer_ic50"          "titer_ic80"#> [19] "response_call"       "nab_lab_source_key"  "lab_code"#> [22] "exp_assayid"         "titer_id50"          "titer_id80"#> [25] "nab_response_id50"   "nab_response_id80"   "slope"#> [28] "vaccine_matched"     "study_prot"          "virus_full_name"#> [31] "virus_species"       "virus_host_cell"     "virus_backbone"

Check outthe referencepageofDataSpaceStudy for all available fields and methods.

Note: The package uses aR6 class to represent theconnection to a study and get around some of R’s copy-on-changebehavior.

• Pleasereport any issues orbugs.
• License: GPL-3
• Get citation information forDataSpaceR in R doingcitation(package = 'DataSpaceR')
• Please note that this project is released with aContributor CodeofConduct.By participating in this project you agree to abide by its terms.