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 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. All created 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.
Most of the assay data found in DataSpace is associated with studies which can be grouped by subject features from inside the web application by users and shared. See the vignette Accessing Studies and Groups for more information.
Connection objects can return DataSpaceMabs and
DataSpaceDonors 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 DataSpace 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$availablePublications.
See the vignette Accessing Publication Data for a tutorial on accessing publication data with DataSpaceR.
DataSpace maintains metadata about all viruses used in Neutralizing Antibody (NAb) assays. This data can be accessed through the app on the NAb antigen page and NAb MAb antigen page.
We can access this metadata in DataSpaceR with
availableViruses:
con$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/17