The DataSpaceR package enables connecting to the CAVD DataSpace (CDS) database in R, making it easier to fetch datasets (NAB, BAMA, MAB, BCRseq, etc.) from specific CAVD (Collaboration for AIDS Vaccine Discovery) studies. The package is a wrapper around Rlabkey.
The examples below are meant to show abridged console output and are not intended to be exhaustive. In order to view the latest and most complete data, please follow the steps below to configure and use DataSpaceR.
There have been some significant changes to DataSpaceR for version 1.0. All instantiated objects can host data from multiple members, for example, studies can be queried in bulk rather than as individual studies. The general API is similar, but users may now pass subsets of tables showing available data to methods that fetch those data instead of passing filter objects or IDs. This new method is similar to filtering the mAb grid in previous versions, which allowed us to supersede that method for getting mAb data, using our new method for getting mAbs across all object types.
You will need a DataSpace account to get started. if you do not have one yet, first go to DataSpace to set up your account. Note that access restrictions may be in place for certain datasets.
In order to connect to the CAVD DataSpace via
DataSpaceR, you will need a netrc file in your
home directory that will contain a machine name (hostname
of DataSpace), and login and password. There
are two ways to create a netrc file.
writeNetrcOn your R console, create a netrc file using a function
from 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.
Make sure you have a valid login and password.
Alternatively, you can manually create a netrc file.
_netrc.netrcSys.getenv("HOME") in RThe following three lines must be included in the .netrc
or _netrc file either separated by white space (spaces,
tabs, or newlines) or commas. Multiple such blocks can exist in one
file.
machine dataspace.cavd.org
login myuser@domain.com
password supersecretpasswordSee here
for more information about netrc.
The cvd256 object shown above is an R6 class,
so it behaves like a true object. Functions, that we will call
“methods”, like loadAvailableDatasets(), are members of the
object, and are accessed using the $ semantic.
In DataSpaceR, get... methods will return an new object,
and load... methods will add some data to an existing
object. There is also the download... verbage used to
descibe a method that will download something from DataSpace to your
computer.
Users can connect to DataSpace using the connectDS()
function described below. This will return a connection object with data
and methods. All objects returned from get... methods from
a connection object inherit the connection object’s data and methods as
well. This makes data operations across objects faster and more
flexible.
A call to connectDS instantiates the connection to DataSpace.
library(DataSpaceR)
con <- connectDS()
con
#> <DataSpaceConnection>
#> URL: https://dataspace.cavd.org
#> User: jmtaylor@scharp.org
#> Available Studies: 397
#> - 79 studies with data
#> - 5074 subjects
#> - 436354 data points
#> Available Groups: 6
#> Available Publications: 1910
#> - 30 publications with data
#> Available Connection objects:
#> - availableDonors
#> - availableGroups
#> - availableMabMixtures
#> - availableMabs
#> - availablePublications
#> - availableStudies
#> - availableViruses
#> - virusNameMappingTables
#> Available Connection methods:
#> - downloadPublicationData
#> - getDaash
#> - getDonors
#> - getGroups
#> - getMabs
#> - getStudiesThe call to connectDS instantiates the connection.
Printing the object shows where it’s connected and the available
studies.
From here, we can choose to preview one of the available objects
and/or apply one of the available connection methods. For example, the
con$availableStudies object contains information about all
the available studies in the CAVD DataSpace. Check out the the
reference page DataSpaceConnection for all available fields and
methods.
con$availableStudies
#> Key: <study_id>
#> study_id short_name
#> <char> <char>
#> 1: cor01 <NA>
#> 2: cvd232 Parks_RV_232
#> 3: cvd234 Zolla-Pazner_Mab_test1 Study
#> 4: cvd235 mAbs potency
#> 5: cvd236 neutralization assays
#> ---
#> 393: vtn910 <NA>
#> 394: vtn913 <NA>
#> 395: vtn914 <NA>
#> 396: vtn915 <NA>
#> 397: x001 <NA>
#> title
#> <char>
#> 1: The correlate of risk targeted intervention study (CORTIS): A randomized, partially-blinded, clinical trial of isoniazid and rifapentine (3HP) therapy to prevent pulmonary tuberculosis in high-risk individuals identified by a transcriptomic correlate of risk
#> 2: Limiting Dose Vaginal SIVmac239 Challenge of RhCMV-SIV vaccinated Indian rhesus macaques.
#> 3: Zolla-Pazner_Mab_Test1
#> 4: Weiss mAbs potency
#> 5: neutralization assays
#> ---
#> 393: A protocol to assess the persistence of vaccine-induced seropositivity in participants who received vaccine in DAIDS-funded preventive HIV vaccine trials
#> 394: Follow-up to an adolescent HIV vaccine preparedness study in South Africa: retention, risk behavior, and HIV incidence
#> 395: A pilot cohort study to evaluate immune responses and activation at the foreskin and rectosigmoid mucosa in Ad5 seropositive HIV-negative Step Study participants
#> 396: A prospective study evaluating the use of self-administered vaginal swabs for the detection of HIV-1 virions among 18 to 25 year-old women in Soweto
#> 397: <NA>
#> type status stage species start_date
#> <char> <char> <char> <char> <Date>
#> 1: Phase III Inactive Assays complete Human <NA>
#> 2: Pre-Clinical NHP Inactive Assays complete Rhesus macaque 2009-11-24
#> 3: Antibody Characterization Inactive Assays complete Non-organism study 2009-02-03
#> 4: Antibody Characterization Inactive Assays complete Non-organism study 2008-08-21
#> 5: Antibody Characterization Active In progress Non-organism study 2009-02-03
#> ---
#> 393: Observational Inactive Follow up complete Human <NA>
#> 394: Preparedness Inactive Concluded, no further activity expected Human <NA>
#> 395: Developmental Inactive Primary analysis complete Human <NA>
#> 396: Developmental Inactive Follow up complete Human <NA>
#> 397: <NA> <NA> <NA> <NA> <NA>
#> strategy network data_availability ni_data_availability
#> <char> <char> <char> <char>
#> 1: <NA> GHDC <NA> <NA>
#> 2: Vector vaccines (viral or bacterial) CAVD <NA> Microarray Data, Treatment assignments
#> 3: Prophylactic neutralizing Ab CAVD <NA> <NA>
#> 4: Prophylactic neutralizing Ab CAVD <NA> <NA>
#> 5: Prophylactic neutralizing Ab CAVD <NA> <NA>
#> ---
#> 393: <NA> HVTN <NA> <NA>
#> 394: <NA> HVTN <NA> <NA>
#> 395: <NA> HVTN <NA> <NA>
#> 396: <NA> HVTN <NA> <NA>
#> 397: <NA> VISC <NA> <NA>The available connection methods can be applied to get data
associated with one or more objects (e.g., studies or mAbs). For
example, we can use con$getStudies to create a connection
to the study cvd256.
cvd256 <- con$getStudies("cvd256")
cvd256
#> <DataSpaceStudies>
#> Studies: cvd256
#> Available integrated datasets:
#> - Binding Ab multiplex assay
#> - Demographics
#> - Neutralizing antibody
#> Available non-integrated datasets:
#> Available publication datasets:
#> Available Studies objects:
#> - availableDatasets
#> - datasets
#> - studies
#> - studyInfo
#> - treatmentArm
#> - variableDefinitions
#> Available Studies methods:
#> - loadAvailableDatasets
#> Available Connection objects:
#> - availableDonors
#> - availableGroups
#> - availableMabMixtures
#> - availableMabs
#> - availablePublications
#> - availableStudies
#> - availableViruses
#> - virusNameMappingTables
#> Available Connection methods:
#> - downloadPublicationData
#> - getDaash
#> - getDonors
#> - getGroups
#> - getMabs
#> - getStudiesPrinting the object shows where it’s connected, to what study, and the available datasets.
cvd256$availableDatasets
#> study_id dataset_type assay_identifier assay_label
#> <char> <char> <char> <char>
#> 1: cvd256 Integrated Assay BAMA Binding Ab multiplex assay
#> 2: cvd256 Integrated Assay Demographics Demographics
#> 3: cvd256 Integrated Assay NAb Neutralizing antibody
cvd256$treatmentArm
#> Key: <arm_id>
#> study_id arm_id arm_part arm_group arm_name randomization coded_label last_day
#> <char> <char> <char> <char> <char> <char> <char> <int>
#> 1: cvd256 cvd256-NA-A-A NA A A Vaccine Group A Vaccine 168
#> 2: cvd256 cvd256-NA-B-B NA B B Vaccine Group B Vaccine 168
#> description
#> <char>
#> 1: DNA-C 4 mg administered IM at weeks 0, 4, and 8 AND NYVAC-C 10^7pfu/mL administered IM at week 24
#> 2: DNA-C 4 mg administered IM at weeks 0 and 4 AND NYVAC-C 10^7pfu/mL administered IM at weeks 20 and 24Available datasets and treatment arm information for the connection
can be accessed by availableDatasets and
treatmentArm.
You may also query availableStudies and pass its results
to the getStudies method.
You may also query availableStudies (or any of the other
availableXXX objects) and pass its results to
getStudies (or any of the other methods). For example, if
you want all available BAMA data from studies in rhesus macaques:
We can load any of the datasets listed in the connection
(availableDatasets). These are loaded to the study
object.
cvd256$loadAvailableDatasets("NAb")
dim(cvd256$datasets$NAb)
#> [1] 1419 33
colnames(cvd256$datasets$NAb)
#> [1] "participant_id" "participant_visit" "visit_day" "assay_identifier" "summary_level"
#> [6] "specimen_type" "antigen" "antigen_type" "virus" "virus_type"
#> [11] "virus_insert_name" "clade" "neutralization_tier" "tier_clade_virus" "target_cell"
#> [16] "initial_dilution" "titer_ic50" "titer_ic80" "response_call" "nab_lab_source_key"
#> [21] "lab_code" "exp_assayid" "titer_id50" "titer_id80" "nab_response_id50"
#> [26] "nab_response_id80" "slope" "vaccine_matched" "study_id" "virus_full_name"
#> [31] "virus_species" "virus_host_cell" "virus_backbone"We may also pass the availableDatasets object to load
datasets to the studies object.
cvd256$availableDatasets[assay_identifier %in% c("BAMA", "Demographics")] |>
cvd256$loadAssayDatasets()
#> Error: attempt to apply non-function
names(
cvd256$datasets
)
#> [1] "NAb"We can view detailed variable information for all datasets loaded
from the variableDefinitions field.
cvd256$variableDefinitions
#> $NAb
#> field_name caption
#> <char> <char>
#> 1: visit_day Visit Day
#> 2: assay_identifier Assay identifier
#> 3: summary_level Data summary level
#> 4: specimen_type Specimen type
#> 5: antigen Antigen name
#> 6: antigen_type Antigen type
#> 7: virus Virus name
#> 8: virus_type Virus type
#> 9: virus_insert_name Virus insert name
#> 10: clade Virus clade
#> 11: neutralization_tier Neutralization tier
#> 12: tier_clade_virus Neutralization tier + Antigen clade + Virus
#> 13: target_cell Target cell
#> 14: initial_dilution Initial dilution
#> 15: titer_ic50 Titer IC50
#> 16: titer_ic80 Titer IC80
#> 17: response_call Response call
#> 18: nab_lab_source_key Data provenance
#> 19: lab_code Lab ID
#> 20: exp_assayid Experimental Assay Design Code
#> 21: slope Slope
#> 22: vaccine_matched Antigen vaccine match indicator
#> 23: virus_full_name Virus full name
#> 24: virus_species Virus species
#> 25: virus_host_cell Virus host cell
#> 26: virus_backbone Virus backbone
#> field_name caption
#> description
#> <char>
#> 1: Target study day defined for a study visit. Study days are relative to Day 0, where Day 0 is typically defined as enrollment and/or first injection.
#> 2: Name identifying assay
#> 3: Defines the level at which the magnitude or response has been summarized (e.g. summarized at the isolate level).
#> 4: The type of specimen used in the assay. For nAb assays, this is generally serum or plasma.
#> 5: The name of the antigen (virus) being tested.
#> 6: The standardized term for the type of virus used in the construction of the nAb antigen.
#> 7: The term for the virus (antigen) being tested.
#> 8: The type of virus used in the construction of the nAb antigen.
#> 9: The amino acid sequence inserted in the virus construct.
#> 10: The clade (gene subtype) of the virus (antigen) being tested.
#> 11: A classification specific to HIV NAb assay design, in which an antigen is assessed for its ease of neutralization (1=most easily neutralized, 3=least easily neutralized)
#> 12: A combination of neutralization tier, antigen clade, and virus used for filtering.
#> 13: The cell line used in the assay to determine infection (lack of neutralization). Generally TZM-bl or A3R5, but can also be other cell lines or non-engineered cells.
#> 14: Indicates the initial specimen dilution.
#> 15: The half maximal inhibitory concentration (IC50).
#> 16: The 80% maximal inhibitory concentration (IC80).
#> 17: Indicates if neutralization is detected.
#> 18: Details regarding the provenance of the assay results.
#> 19: A code indicating the lab performing the assay.
#> 20: Unique ID assigned to the experiment design of the assay for tracking purposes.
#> 21: The slope calculated using the difference between 50% and 80% neutralization.
#> 22: Indicates if the interactive part of the antigen was designed to match the immunogen in the vaccine.
#> 23: The full name of the virus used in the construction of the nAb antigen.
#> 24: A classification for virus species using informal taxonomy.
#> 25: The host cell used to incubate the virus stock.
#> 26: Indicates the backbone used to generate the virus if from a different plasmid than the envelope.
#> descriptionA group is a curated collection of participants from filtering of treatments, products, studies, or species, and it is created in the DataSpace App.
Using the DataSpace application, you may filter and visualize data
and save them for later as a “group” using the application Active
Filters dialog. You may also explore those groups in R with
DataSpaceR
We can browse saved groups via availableGroups.
con$availableGroups
#> Key: <group_id>
#> group_id label original_label
#> <int> <char> <char>
#> 1: 220 NYVAC durability comparison NYVAC_durability
#> 2: 228 HVTN 505 case control subjects HVTN 505 case control subjects
#> 3: 230 HVTN 505 polyfunctionality vs BAMA HVTN 505 polyfunctionality vs BAMA
#> 4: 256 CAVD 239 integrated data CAVD 239 integrated data
#> 5: 292 testing testing
#> 6: 293 testing2 testing2
#> description
#> <char>
#> 1: Compare durability in 4 NHP studies using NYVAC-C (vP2010) and NYVAC-KC-gp140 (ZM96) products.
#> 2: Participants from HVTN 505 included in the case-control analysis
#> 3: Compares ICS polyfunctionality (CD8+, Any Env) to BAMA mfi-delta (single Env antigen) in the HVTN 505 case control cohort
#> 4: Integrated study data for CAVD 239, including integrated assay data, demographics, and treatment group information.
#> 5: <NA>
#> 6: <NA>
#> created_by shared n studies
#> <char> <lgcl> <int> <char>
#> 1: ehenrich TRUE 78 cvd281, cvd434, cvd259, cvd277
#> 2: drienna TRUE 189 vtn505
#> 3: drienna TRUE 170 vtn505
#> 4: drienna TRUE 38 cvd239
#> 5: jmtaylor FALSE 238 vtn505
#> 6: jmtaylor FALSE 1253 vtn505To fetch data from a saved group, create a connection at the project
level with a group ID. For example, we can connect to the “NYVAC
durability comparison” group which has group ID 220 by
getGroup.
nyvac <- con$getGroups(220)
nyvac
#> <DataSpaceGroups>
#> Groups: NYVAC durability comparison
#> Available integrated datasets:
#> - Binding Ab multiplex assay
#> - Demographics
#> - Enzyme-Linked ImmunoSpot
#> - Intracellular Cytokine Staining
#> - Neutralizing antibody
#> Available Groups objects:
#> - datasets
#> - donorMetadata
#> - mabMetadata
#> - mabMix
#> - mabMixMetadata
#> - variableDefinitions
#> Available Connection objects:
#> - availableDonors
#> - availableGroups
#> - availableMabMixtures
#> - availableMabs
#> - availablePublications
#> - availableStudies
#> - availableViruses
#> - virusNameMappingTables
#> Available Connection methods:
#> - downloadPublicationData
#> - getDaash
#> - getDonors
#> - getGroups
#> - getMabs
#> - getStudiesOr passing a filtered availableGroups object to
getGroup.
nyvac <- con$availableGroups[label %in% c("NYVAC durability comparison")] |>
con$getGroups()
nyvac
#> <DataSpaceGroups>
#> Groups: NYVAC durability comparison
#> Available integrated datasets:
#> - Binding Ab multiplex assay
#> - Demographics
#> - Enzyme-Linked ImmunoSpot
#> - Intracellular Cytokine Staining
#> - Neutralizing antibody
#> Available Groups objects:
#> - datasets
#> - donorMetadata
#> - mabMetadata
#> - mabMix
#> - mabMixMetadata
#> - variableDefinitions
#> Available Connection objects:
#> - availableDonors
#> - availableGroups
#> - availableMabMixtures
#> - availableMabs
#> - availablePublications
#> - availableStudies
#> - availableViruses
#> - virusNameMappingTables
#> Available Connection methods:
#> - downloadPublicationData
#> - getDaash
#> - getDonors
#> - getGroups
#> - getMabs
#> - getStudiesUnlike the studies object, a group object automatically loads any datasets associated with the groups retrieved from DataSpace.
DataSpace maintains metadata about all viruses used in Neutralizing Antibody (NAb) assays. This data can be accessed through the app on the NAb antigen page and NAb MAb antigen page.
We can access this metadata in DataSpaceR with
availableViruses:
con$availableViruses
#> Key: <cds_virus_id>
#> cds_virus_id virus virus_full_name virus_backbone virus_host_cell virus_plot_label
#> <char> <char> <char> <char> <char> <char>
#> 1: cds_1 0013095-2.11 0013095-2.11 [SG3Δenv] 293T/17 SG3Δenv 293T/17 0013095-2.11
#> 2: cds_10 0984.V2.C2 0984.V2.C2 [SG3Δenv] 293T/17 SG3Δenv 293T/17 <NA>
#> 3: cds_100 B005018-8_F6.3 B005018-8_F6.3 [SG3Δenv] 293T/17 SG3Δenv 293T/17 <NA>
#> 4: cds_101 B005582-7_G7.8 B005582-7_G7.8 [SG3Δenv] 293T/17 SG3Δenv 293T/17 B005582
#> 5: cds_102 BaL.26 BaL.26 [SG3Δenv] 293T/17 SG3Δenv 293T/17 BaL.26
#> ---
#> 799: cds_94 92BR025.9 92BR025.9 [SG3Δenv] 293T/17 SG3Δenv 293T/17 <NA>
#> 800: cds_95 933.v4.c4 933.v4.c4 [SG3Δenv] 293T/17 SG3Δenv 293T/17 <NA>
#> 801: cds_97 98-F4_H5_13 98-F4_H5_13 [SG3Δenv] 293T/17 SG3Δenv 293T/17 <NA>
#> 802: cds_98 A07412M1.vrc12 A07412M1.vrc12 [SG3Δenv] 293T/17 SG3Δenv 293T/17 <NA>
#> 803: cds_99 AC10.0.29 AC10.0.29 [SG3Δenv] 293T/17 SG3Δenv 293T/17 AC10.0.29
#> virus_type virus_species clade neutralization_tier
#> <char> <char> <char> <char>
#> 1: Env Pseudotype HIV <NA> 2
#> 2: Env Pseudotype HIV C 3
#> 3: Env Pseudotype HIV C 2
#> 4: Env Pseudotype HIV C <NA>
#> 5: Env Pseudotype HIV B 1B
#> ---
#> 799: Env Pseudotype HIV C <NA>
#> 800: Env Pseudotype HIV C 3
#> 801: Env Pseudotype HIV C 3
#> 802: Env Pseudotype HIV D 2
#> 803: Env Pseudotype HIV B 2
#> virus_name_other
#> <char>
#> 1: <NA>
#> 2: 0984.v2.c2
#> 3: <NA>
#> 4: B005582, B005582-27_G7.8
#> 5: BaL.26_TM, Bal.26, Bal.26 [SG3<94>~env] 293T/17, Bal.26 [SG3Δenv] 293T, HIV Bal.26, HIV Bal.26[-Luc]293T, HIV Bal.26[SG3<94>~env]293T/17, SG3�~env, SHIV 1157ipd3N4.3
#> ---
#> 799: 92BR025.9 [SG3<94>~env] 293T, 92BR025.9 [SG3<94>~env] 293T/17, HIV 92BR025.9, HIV 92BR025.9[SG3<94>~env]293T, HIV 92BR025.9[SG3<94>~env]293T/17, SG3�~env
#> 800: <NA>
#> 801: 98-F4_H5-13
#> 802: A07412M1.vrc12---349, A07412M1_VRC12
#> 803: AC10.0.29 [SG3<94>~env] 293T/17, AC10.0.29---451, HIV AC10.0.29, HIV AC10.0.29[SG3<94>~env]293T/17Connection objects can return DataSpaceMab and
DataSpaceDonor objects which are used to access mAb related
data. See the vignette Accessing
Monoclonal Antibody Data for more information.
The Database of Annotation Antibodies for HIV-1, or DAASH for short,
can be accessed though mAb objects, or donor objects, or more directly
via a DataSpaceDaash object. See the vigette Accessing CDS DAASH for more
information.
DataSpace maintains a curated collection of relevant publications,
which can be accessed through the Publications
page through the app. Metadata about these publications can be
accessed through DataSpaceR with
con$availablePublications.
See the vignette Accessing Publication Data for a tutorial on accessing publication data with DataSpaceR.