Usespurrr::modify_at to apply a set of methods at specific locations in a
list.
Usage
prep_for_json(x, prep_methods_list = prep_methods())Examples
wddsWizard::becker_project_metadata |>
prep_for_json()
#> $creators
#> $creators[[1]]
#> name givenName familyName
#> [x] Daniel J. Becker Daniel J. Becker
#> affiliation
#> [x] Department of Biology, University of Oklahoma, Norman, OK, USA, https://ror.org/02aqsxs83
#> nameIdentifiers
#> [x] https://orcid.org/0000-0003-4315-8628, ORCID
#>
#> $creators[[2]]
#> name givenName familyName
#> [x] Guang-Sheng Lei Guang-Sheng Lei
#> affiliation
#> [x] Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA, https://ror.org/02ets8c94
#>
#>
#> $descriptions
#> $descriptions[[1]]
#> description
#> [x] Bats can harbor many pathogens without showing disease. However, the mechanisms by which bats resolve these infections or limit pathology remain unclear. To illuminate the bat immune response to coronaviruses, viruses with high public health significance, we will use serum proteomics to assess broad differences in immune proteins of uninfected and infected vampire bats (Desmodus rotundus). In contrast to global profiling techniques of blood such as transcriptomics, proteomics provides a unique perspective into immunology, as the serum proteome includes proteins from not only blood but also those secreted from proximal tissues. Here, we expand our recent work on the serum proteome of wild vampire bats (Desmodus rotundus) to better understand CoV pathogenesis. Across 19 bats sampled in 2019 in northern Belize with available sera, we detected CoVs in oral or rectal swabs from four individuals. We used data independent acquisition-based mass spectrometry to profile and compare the undepleted serum proteome of these 19 bats. These results will provide much needed insight into changes in the bat serum proteome in response to coronavirus infection.
#> descriptionType
#> [x] Abstract
#>
#>
#> $fundingReferences
#> $fundingReferences[[1]]
#> funderName funderIdentifier
#> [x] National Geographic Society http://dx.doi.org/10.13039/100006733
#> awardNumber
#> [x] NGS-55503R-19
#>
#> $fundingReferences[[2]]
#> funderName funderIdentifier
#> [x] Indiana University http://dx.doi.org/10.13039/100006733
#>
#> $fundingReferences[[3]]
#> funderName funderIdentifier
#> [x] College of Charleston http://dx.doi.org/10.13039/100009789
#>
#>
#> $identifier
#> $identifier[[1]]
#> identifier identifierType
#> [x] 10.5072/zenodo.168108 DOI
#>
#>
#> $language
#> [x] "en"
#>
#> $methodology
#> $methodology$eventBased
#> [x] false
#>
#> $methodology$archival
#> [x] false
#>
#>
#> $publicationYear
#> [x] "2022"
#>
#> $relatedIdentifiers
#> $relatedIdentifiers[[1]]
#> relatedIdentifier
#> [x] https://pharos.viralemergence.org/projects/?prj=prjRPayEvMecN
#> relatedIdentifierType relationType
#> [x] URL IsVersionOf
#>
#> $relatedIdentifiers[[2]]
#> relatedIdentifier relatedIdentifierType relationType
#> [x] 10.3389/fviro.2022.862961 DOI IsPartOf
#>
#>
#> $rights
#> $rights[[1]]
#> rights
#> [x] CC0
#>
#>
#> $subjects
#> $subjects[[1]]
#> subject
#> [x] Proteomics
#>
#> $subjects[[2]]
#> subject
#> [x] Immune Response
#>
#>
#> $titles
#> $titles[[1]]
#> title
#> [x] Serum proteomics of coronavirus shedding in vampire bats (Desmodus rotundus)
#>
#>
a <- list("hello_world" = 1:10 )
methods_list <- list("hello_world" = function(x){x*2},
"unused_method" = function(x){x/2})
prep_for_json(a,methods_list)
#> $hello_world
#> [1] 2 4 6 8 10 12 14 16 18 20
#>