Type: Package
Title: Create and Manipulate BioCompute Objects
Version: 1.1.1
Maintainer: Soner Koc <soner.koc@sevenbridges.com>
Description: Tools to create, validate, and export BioCompute Objects described in King et al. (2019) <doi:10.17605/osf.io/h59uh>. Users can encode information in data frames, and compose BioCompute Objects from the domains defined by the standard. A checksum validator and a JSON schema validator are provided. This package also supports exporting BioCompute Objects as JSON, PDF, HTML, or 'Word' documents, and exporting to cloud-based platforms.
License: AGPL-3
VignetteBuilder: knitr
URL: https://sbg.github.io/biocompute/, https://github.com/sbg/biocompute
BugReports: https://github.com/sbg/biocompute/issues
Encoding: UTF-8
Imports: methods, jsonlite, yaml, digest, uuid, jsonvalidate, httr, curl, crayon, cli, stringr, magrittr, rmarkdown
Suggests: knitr
RoxygenNote: 7.1.2
NeedsCompilation: no
Packaged: 2022-04-01 15:14:46 UTC; c02ck1a7lvdm
Author: Soner Koc ORCID iD [aut, cre], Jeffrey Grover ORCID iD [aut], Nan Xiao ORCID iD [aut], Dennis Dean ORCID iD [aut], Seven Bridges Genomics [cph, fnd]
Repository: CRAN
Date/Publication: 2022-05-03 07:00:27 UTC

biocompute: Create and Manipulate BioCompute Objects

Description

Tools to create, validate, and export BioCompute Objects described in King et al. (2019) <doi:10.17605/osf.io/h59uh>. Users can encode information in data frames, and compose BioCompute Objects from the domains defined by the standard. A checksum validator and a JSON schema validator are provided. This package also supports exporting BioCompute Objects as JSON, PDF, HTML, or 'Word' documents, and exporting to cloud-based platforms.

Author(s)

Maintainer: Soner Koc soner.koc@sevenbridges.com (ORCID)

Authors:

Other contributors:

See Also

Useful links:

Pipe operator

Description

See magrittr::%>% for details.

Usage

lhs %>% rhs

Compose BioCompute Object - Description Domain (v1.4.2)

Description

Compose BioCompute Object - Description Domain (v1.4.2)

Usage

compose_description_v1.4.2(
  keywords = NULL,
  xref = NULL,
  platform = list("Seven Bridges Platform"),
  pipeline_meta = NULL,
  pipeline_prerequisite = NULL,
  pipeline_input = NULL,
  pipeline_output = NULL
)

compose_description(
  keywords = NULL,
  xref = NULL,
  platform = list("Seven Bridges Platform"),
  pipeline_meta = NULL,
  pipeline_prerequisite = NULL,
  pipeline_input = NULL,
  pipeline_output = NULL
)

Arguments

keywords

Character vector. A list of keywords to aid in searchability and description of the experiment.

xref

Data frame. A list of the databases and/or ontology IDs that are cross-referenced in the BCO.

platform

Character string or list. Reference to a particular deployment of an existing platform where this BCO can be reproduced.

pipeline_meta

Data frame. Pipeline metadata. Variables include step_number, name, description, and version.

pipeline_prerequisite

Data frame. Packages or prerequisites for running the tools used. Variables include step_number, name, uri, and access_time.

pipeline_input

Data frame. Input files for the tools. Variables include step_number, uri, and access_time.

pipeline_output

Data frame. Output files for the tools. Variables include step_number, uri, and access_time.

Value

A list of class bco.domain

Examples

keywords <- c("HCV1a", "Ledipasvir", "antiviral resistance", "SNP", "amino acid substitutions")
xref <- data.frame(
  "namespace" = c("pubchem.compound", "pubmed", "so", "taxonomy"),
  "name" = c("PubChem-compound", "PubMed", "Sequence Ontology", "Taxonomy"),
  "ids" = I(list(
    "67505836",
    "26508693",
    c("SO:000002", "SO:0000694", "SO:0000667", "SO:0000045"),
    "31646"
  )),
  "access_time" = c(
    as.POSIXct("2017-01-20T09:40:17", format = "%Y-%m-%dT%H:%M:%S", tz = "EST"),
    as.POSIXct("2017-01-21T09:40:17", format = "%Y-%m-%dT%H:%M:%S", tz = "EST"),
    as.POSIXct("2017-01-22T09:40:17", format = "%Y-%m-%dT%H:%M:%S", tz = "EST"),
    as.POSIXct("2017-01-23T09:40:17", format = "%Y-%m-%dT%H:%M:%S", tz = "EST")
  ),
  stringsAsFactors = FALSE
)

platform <- "Seven Bridges Platform"

pipeline_meta <- data.frame(
  "step_number" = c("1"),
  "name" = c("HIVE-hexagon"),
  "description" = c("Alignment of reads to a set of references"),
  "version" = c("1.3"),
  stringsAsFactors = FALSE
)

pipeline_prerequisite <- data.frame(
  "step_number" = rep("1", 5),
  "name" = c(
    "Hepatitis C virus genotype 1",
    "Hepatitis C virus type 1b complete genome",
    "Hepatitis C virus (isolate JFH-1) genomic RNA",
    "Hepatitis C virus clone J8CF, complete genome",
    "Hepatitis C virus S52 polyprotein gene"
  ),
  "uri" = c(
    "https://www.ncbi.nlm.nih.gov/nuccore/22129792",
    "https://www.ncbi.nlm.nih.gov/nuccore/5420376",
    "https://www.ncbi.nlm.nih.gov/nuccore/13122261",
    "https://www.ncbi.nlm.nih.gov/nuccore/386646758",
    "https://www.ncbi.nlm.nih.gov/nuccore/295311559"
  ),
  "access_time" = c(
    as.POSIXct("2017-01-24T09:40:17", format = "%Y-%m-%dT%H:%M:%S", tz = "EST"),
    as.POSIXct("2017-01-24T09:40:17", format = "%Y-%m-%dT%H:%M:%S", tz = "EST"),
    as.POSIXct("2017-01-24T09:40:17", format = "%Y-%m-%dT%H:%M:%S", tz = "EST"),
    as.POSIXct("2017-01-24T09:40:17", format = "%Y-%m-%dT%H:%M:%S", tz = "EST"),
    as.POSIXct("2017-01-24T09:40:17", format = "%Y-%m-%dT%H:%M:%S", tz = "EST")
  ),
  stringsAsFactors = FALSE
)

pipeline_input <- data.frame(
  "step_number" = rep("1", 2),
  "uri" = c(
    "https://example.com/dna.cgi?cmd=objFile&ids=514683",
    "https://example.com/dna.cgi?cmd=objFile&ids=514682"
  ),
  "access_time" = c(
    as.POSIXct("2017-01-24T09:40:17", format = "%Y-%m-%dT%H:%M:%S", tz = "EST"),
    as.POSIXct("2017-01-24T09:40:17", format = "%Y-%m-%dT%H:%M:%S", tz = "EST")
  ),
  stringsAsFactors = FALSE
)

pipeline_output <- data.frame(
  "step_number" = rep("1", 2),
  "uri" = c(
    "https://example.com/data/514769/allCount-aligned.csv",
    "https://example.com/data/514801/SNPProfile*.csv"
  ),
  "access_time" = c(
    as.POSIXct("2017-01-24T09:40:17", format = "%Y-%m-%dT%H:%M:%S", tz = "EST"),
    as.POSIXct("2017-01-24T09:40:17", format = "%Y-%m-%dT%H:%M:%S", tz = "EST")
  ),
  stringsAsFactors = FALSE
)

compose_description(
  keywords, xref, platform,
  pipeline_meta, pipeline_prerequisite, pipeline_input, pipeline_output
) %>% convert_json()

Compose BioCompute Object - Error Domain (v1.4.2)

Description

The error domain can be used to determine what range of input returns outputs that are within the tolerance level defined in this subdomain and therefore can be used to optimize algorithm (domain definition).

Usage

compose_error_v1.4.2(empirical = NULL, algorithmic = NULL)

compose_error(empirical = NULL, algorithmic = NULL)

Arguments

empirical

Data frame. Variables include key and value. Each row is one item in the empirical error subdomain.

algorithmic

Data frame. Variables include key and value. Each row is one item in the algorithmic subdomain.

Value

A list of class bco.domain

Examples

empirical <- data.frame(
  "key" = c("false_negative_alignment_hits", "false_discovery"),
  "value" = c("<0.0010", "<0.05"),
  stringsAsFactors = FALSE
)

algorithmic <- data.frame(
  "key" = c("false_positive_mutation_calls", "false_discovery"),
  "value" = c("<0.00005", "0.005"),
  stringsAsFactors = FALSE
)

compose_error(empirical, algorithmic) %>% convert_json()

Compose BioCompute Object - Execution Domain (v1.4.2)

Description

Compose BioCompute Object - Execution Domain (v1.4.2)

Usage

compose_execution_v1.4.2(
  script = NULL,
  script_driver = NULL,
  software_prerequisites = NULL,
  external_data_endpoints = NULL,
  environment_variables = NULL
)

compose_execution(
  script = NULL,
  script_driver = NULL,
  software_prerequisites = NULL,
  external_data_endpoints = NULL,
  environment_variables = NULL
)

Arguments

script

Character string or list. Points to internal or external references to an object that was used to perform computations for this BCO instance.

script_driver

Character string. Indicate what kind of executable can be launched in order to perform a sequence of commands described in the script in order to run the pipeline.

software_prerequisites

Data frame. The minimal necessary prerequisites, library, and tool versions needed to successfully run the script to produce BCO. Variables include name, version, uri, access_time, and sha1_chksum. Each row is one item in the output subdomain.

external_data_endpoints

Data frame. The minimal necessary domain-specific external data source access to successfully run the script to produce the BCO. Variables include mediatype, name, and url. Each row is one item in the output subdomain.

environment_variables

Data frame. Key-value pairs useful to configure the execution environment on the target platform. Variables include key and value.

Value

A list of class bco.domain

Examples

script <- "https://example.com/workflows/antiviral_resistance_detection_hive.py"
script_driver <- "shell"
software_prerequisites <- data.frame(
  "name" = c("HIVE-hexagon", "HIVE-heptagon"),
  "version" = c("babajanian.1", "albinoni.2"),
  "uri" = c(
    "https://example.com/dna.cgi?cmd=dna-hexagon&cmdMode=-",
    "https://example.com/dna.cgi?cmd=dna-heptagon&cmdMode=-"
  ),
  "access_time" = c(
    as.POSIXct("2017-01-24T09:40:17", format = "%Y-%m-%dT%H:%M:%S", tz = "EST"),
    as.POSIXct("2017-01-24T09:40:17", format = "%Y-%m-%dT%H:%M:%S", tz = "EST")
  ),
  "sha1_chksum" = c("d60f506cddac09e9e816531e7905ca1ca6641e3c", NA),
  stringsAsFactors = FALSE
)
external_data_endpoints <- data.frame(
  "name" = c("generic name", "access to ftp server", "access to e-utils web service"),
  "url" = c(
    "protocol://domain:port/application/path",
    "ftp://data.example.com:21/",
    "https://eutils.ncbi.nlm.nih.gov/entrez/eutils"
  ),
  stringsAsFactors = FALSE
)
environment_variables <- data.frame(
  "key" = c("HOSTTYPE", "EDITOR"),
  "value" = c("x86_64-linux", "vim")
)

compose_execution(
  script, script_driver, software_prerequisites, external_data_endpoints, environment_variables
) %>% convert_json()

Compose BioCompute Object - Extension Domain (v1.4.2)

Description

Compose BioCompute Object - Extension Domain (v1.4.2)

Usage

compose_extension_v1.4.2(fhir = NULL, scm = NULL)

compose_extension(fhir = NULL, scm = NULL)

Arguments

fhir

FHIR extension domain composed by compose_fhir.

scm

SCM extension domain composed by compose_scm.

Value

A list of class bco.domain

Examples

fhir_endpoint <- "https://fhirtest.uhn.ca/baseDstu3"
fhir_version <- "3"
fhir_resources <- data.frame(
  "id" = c("21376", "6288583", "25544", "92440", "4588936"),
  "resource" = c(
    "Sequence", "DiagnosticReport", "ProcedureRequest",
    "Observation", "FamilyMemberHistory"
  ),
  stringsAsFactors = FALSE
)

fhir <- compose_fhir(fhir_endpoint, fhir_version, fhir_resources)

scm_repository <- "https://github.com/example/repo"
scm_type <- "git"
scm_commit <- "c9ffea0b60fa3bcf8e138af7c99ca141a6b8fb21"
scm_path <- "workflow/hive-viral-mutation-detection.cwl"
scm_preview <- "https://github.com/example/repo/blob/master/mutation-detection.cwl"

scm <- compose_scm(scm_repository, scm_type, scm_commit, scm_path, scm_preview)

compose_extension(fhir, scm) %>% convert_json()

Compose BioCompute Object - FHIR Extension (v1.4.2)

Description

Compose BioCompute Object - FHIR Extension (v1.4.2)

Usage

compose_fhir_v1.4.2(endpoint = NULL, version = NULL, resources = NULL)

compose_fhir(endpoint = NULL, version = NULL, resources = NULL)

Arguments

endpoint

Character string. The URL of the endpoint of the FHIR server containing the resource.

version

Character string. The FHIR version used.

resources

Data frame with two variables: id and resource. Each row is one item of resources to fetch from the endpoint.

Value

A list of class bco.domain

Examples

fhir_endpoint <- "https://fhirtest.uhn.ca/baseDstu3"
fhir_version <- "3"
fhir_resources <- data.frame(
  "id" = c("21376", "6288583", "25544", "92440", "4588936"),
  "resource" = c(
    "Sequence", "DiagnosticReport", "ProcedureRequest",
    "Observation", "FamilyMemberHistory"
  ),
  stringsAsFactors = FALSE
)

compose_fhir(fhir_endpoint, fhir_version, fhir_resources) %>% convert_json()

Compose BioCompute Object - Input and Output Domain (v1.4.2)

Description

This domain contains the list of global input and output files created by the computational workflow, excluding the intermediate files.

Usage

compose_io_v1.4.2(input = NULL, output = NULL)

compose_io(input = NULL, output = NULL)

Arguments

input

Data frame. Variables include filename, uri, and access_time. Each row is one item in the input subdomain.

output

Data frame. Variables include mediatype, uri, and access_time. Each row is one item in the output subdomain.

Value

A list of class bco.domain

Examples

input_subdomain <- data.frame(
  "filename" = c(
    "Hepatitis C virus genotype 1",
    "Hepatitis C virus type 1b complete genome"
  ),
  "uri" = c(
    "https://www.ncbi.nlm.nih.gov/nuccore/22129792",
    "https://www.ncbi.nlm.nih.gov/nuccore/5420376"
  ),
  "access_time" = c(
    as.POSIXct("2017-01-24T09:40:17", format = "%Y-%m-%dT%H:%M:%S", tz = "EST"),
    as.POSIXct("2017-01-24T09:40:17", format = "%Y-%m-%dT%H:%M:%S", tz = "EST")
  ),
  stringsAsFactors = FALSE
)

output_subdomain <- data.frame(
  "mediatype" = c("text/csv", "text/csv"),
  "uri" = c(
    "https://example.com/data/514769/dnaAccessionBased.csv",
    "https://example.com/data/514801/SNPProfile*.csv"
  ),
  "access_time" = c(
    as.POSIXct("2017-01-24T09:40:17", format = "%Y-%m-%dT%H:%M:%S", tz = "EST"),
    as.POSIXct("2017-01-24T09:40:17", format = "%Y-%m-%dT%H:%M:%S", tz = "EST")
  ),
  stringsAsFactors = FALSE
)

compose_io(input_subdomain, output_subdomain) %>% convert_json()

Compose BioCompute Object - Parametric Domain (v1.4.2)

Description

Non-default parameters customizing the computational flow which can affect the output of the calculations (domain definition).

Usage

compose_parametric_v1.4.2(df = NULL)

compose_parametric(df = NULL)

Arguments

df

Data frame. Variables include param (parameter names), value (value of the parameters), and step (step number for each parameter).

Value

A list of class bco.domain

Examples

df_parametric <- data.frame(
  "param" = c(
    "seed", "minimum_match_len",
    "divergence_threshold_percent",
    "minimum_coverage", "freq_cutoff"
  ),
  "value" = c("14", "66", "0.30", "15", "0.10"),
  "step" = c(1, 1, 1, 2, 2)
)

compose_parametric(df_parametric) %>% convert_json()

Compose BioCompute Object - Provenance Domain (v1.4.2)

Description

Compose BioCompute Object - Provenance Domain (v1.4.2)

Usage

compose_provenance_v1.4.2(
  name = NULL,
  version = NULL,
  review = NULL,
  derived_from = NULL,
  obsolete_after = NULL,
  embargo = NULL,
  created = NULL,
  modified = NULL,
  contributors = NULL,
  license = NULL
)

compose_provenance(
  name = NULL,
  version = NULL,
  review = NULL,
  derived_from = NULL,
  obsolete_after = NULL,
  embargo = NULL,
  created = NULL,
  modified = NULL,
  contributors = NULL,
  license = NULL
)

Arguments

name

Character string. Name for the BCO.

version

Character string. Version of this BCO instance object. Should follow the Semantic Versioning format (MAJOR.MINOR.PATCH).

review

Data frame. Reviewer identifiers and descriptions of the status of an object in the review process.

derived_from

Character string. Inheritance/derivation description.

obsolete_after

Date-time object. Expiration date of the object (optional).

embargo

Vector of date-time objects start_time and end_time. If the object has a period of time that it is not public, that range can be specified with this.

created

Date-time object. Initial creation time of the object.

modified

Date-time object. The most recent modification time of the object.

contributors

Data frame. Contributor identifiers and descriptions of their contribution types.

license

Character string. Licence URL or other licence information (text).

Value

A list of class bco.domain

Examples

name <- "HCV1a ledipasvir resistance SNP detection"
version <- "1.0.0"
review <- data.frame(
  "status" = c("approved", "approved"),
  "reviewer_comment" = c(
    "Approved by [company name] staff. Waiting for approval from FDA Reviewer",
    "The revised BCO looks fine"
  ),
  "date" = c(
    as.POSIXct("2017-11-12T12:30:48", format = "%Y-%m-%dT%H:%M:%S", tz = "EST"),
    as.POSIXct("2017-12-12T12:30:48", format = "%Y-%m-%dT%H:%M:%S", tz = "America/Los_Angeles")
  ),
  "reviewer_name" = c("Jane Doe", "John Doe"),
  "reviewer_affiliation" = c("Seven Bridges Genomics", "U.S. Food and Drug Administration"),
  "reviewer_email" = c("example@sevenbridges.com", "example@fda.gov"),
  "reviewer_contribution" = c("curatedBy", "curatedBy"),
  "reviewer_orcid" = c("https://orcid.org/0000-0000-0000-0000", NA),
  stringsAsFactors = FALSE
)

derived_from <- "https://github.com/biocompute-objects/BCO_Specification/blob/1.2.1-beta/HCV1a.json"
obsolete_after <- as.POSIXct("2018-11-12T12:30:48", format = "%Y-%m-%dT%H:%M:%S", tz = "EST")

embargo <- c(
  "start_time" = as.POSIXct("2017-10-12T12:30:48", format = "%Y-%m-%dT%H:%M:%S", tz = "EST"),
  "end_time" = as.POSIXct("2017-11-12T12:30:48", format = "%Y-%m-%dT%H:%M:%S", tz = "EST")
)

created <- as.POSIXct("2017-01-20T09:40:17", format = "%Y-%m-%dT%H:%M:%S", tz = "EST")

modified <- as.POSIXct("2019-05-10T09:40:17", format = "%Y-%m-%dT%H:%M:%S", tz = "EST")

contributors <- data.frame(
  "name" = c("Jane Doe", "John Doe"),
  "affiliation" = c("Seven Bridges Genomics", "U.S. Food and Drug Administration"),
  "email" = c("example@sevenbridges.com", "example@fda.gov"),
  "contribution" = I(list(c("createdBy", "curatedBy"), c("authoredBy"))),
  "orcid" = c("https://orcid.org/0000-0000-0000-0000", NA),
  stringsAsFactors = FALSE
)

license <- "https://creativecommons.org/licenses/by/4.0/"

compose_provenance(
  name, version, review, derived_from, obsolete_after,
  embargo, created, modified, contributors, license
) %>% convert_json()

Compose BioCompute Object - SCM Extension (v1.4.2)

Description

Compose BioCompute Object - SCM Extension (v1.4.2)

Usage

compose_scm_v1.4.2(
  scm_repository = NULL,
  scm_type = c("git", "svn", "hg", "other"),
  scm_commit = NULL,
  scm_path = NULL,
  scm_preview = NULL
)

compose_scm(
  scm_repository = NULL,
  scm_type = c("git", "svn", "hg", "other"),
  scm_commit = NULL,
  scm_path = NULL,
  scm_preview = NULL
)

Arguments

scm_repository

Character string. Base URL of the SCM repository.

scm_type

Character string. Type of SCM database. Must be one of "git", "svn", "hg", or "other".

scm_commit

Character string. Revision within the SCM repository. Should be a repository-wide commit identifier or name of a tag, but may be a name of a branch.

scm_path

Character string. Path from the repository to the source code referenced. Should not start with /.

scm_preview

Character string. The full URI for the source code referenced by the BioCompute Object.

Value

A list of class bco.domain

Examples

scm_repository <- "https://github.com/example/repo"
scm_type <- "git"
scm_commit <- "c9ffea0b60fa3bcf8e138af7c99ca141a6b8fb21"
scm_path <- "workflow/hive-viral-mutation-detection.cwl"
scm_preview <- "https://github.com/example/repo/blob/master/mutation-detection.cwl"

compose_scm(scm_repository, scm_type, scm_commit, scm_path, scm_preview) %>% convert_json()

Compose BioCompute Object - Top Level Fields (v1.4.2)

Description

Compose BioCompute Object - Top Level Fields (v1.4.2)

Usage

compose_tlf_v1.4.2(
  provenance,
  usability,
  extension,
  description,
  execution,
  parametric,
  io,
  error,
  object_id = NULL
)

compose_tlf(
  provenance,
  usability,
  extension,
  description,
  execution,
  parametric,
  io,
  error,
  object_id = NULL
)

Arguments

provenance

Provenance domain

usability

Usability domain

extension

Extension domain

description

Description domain

execution

Execution domain

parametric

Parametric domain

io

I/O domain

error

Error domain

object_id

BioCompute Object identifier (definition). If NULL, will use a UUID generated by generate_id.

Value

A vector of top level fields

Examples

compose_tlf(
  compose_provenance(), compose_usability(), compose_extension(),
  compose_description(), compose_execution(), compose_parametric(),
  compose_io(), compose_error()
) %>% convert_json()

Compose BioCompute Object - Usability Domain (v1.4.2)

Description

The usability domain (domain definition).

Usage

compose_usability_v1.4.2(text = NULL)

compose_usability(text = NULL)

Arguments

text

A character vector of free text values that could improves search-ability, provide specific scientific use cases, and a description of the function of the object.

Value

A list of class bco.domain

Examples

text <- c(
  paste(
    "Identify baseline single nucleotide polymorphisms (SNPs)[SO:0000694]",
    "(insertions)[SO:0000667], and (deletions)[SO:0000045] that correlate",
    "with reduced (ledipasvir)[pubchem.compound:67505836] antiviral drug",
    "efficacy in (Hepatitis C virus subtype 1)[taxonomy:31646]"
  ),
  paste(
    "Identify treatment emergent amino acid (substitutions)[SO:1000002]",
    "that correlate with antiviral drug treatment failure"
  ),
  paste(
    "Determine whether the treatment emergent amino acid",
    "(substitutions)[SO:1000002] identified correlate with treatment",
    "failure involving other drugs against the same virus"
  )
)

text %>%
  compose_usability() %>%
  convert_json()

Compose BioCompute Object (v1.4.2)

Description

Compose BioCompute Object (v1.4.2)

Usage

compose_v1.4.2(
  tlf,
  provenance,
  usability,
  extension,
  description,
  execution,
  parametric,
  io,
  error
)

compose(
  tlf,
  provenance,
  usability,
  extension,
  description,
  execution,
  parametric,
  io,
  error
)

Arguments

tlf

Top level fields

provenance

Provenance domain

usability

Usability domain

extension

Extension domain

description

Description domain

execution

Execution domain

parametric

Parametric domain

io

I/O domain

error

Error domain

Value

A list of class bco

Examples

tlf <- compose_tlf(
  compose_provenance(), compose_usability(), compose_extension(),
  compose_description(), compose_execution(), compose_parametric(),
  compose_io(), compose_error()
)
biocompute::compose(
  tlf,
  compose_provenance(), compose_usability(), compose_extension(),
  compose_description(), compose_execution(), compose_parametric(),
  compose_io(), compose_error()
) %>% convert_json()

Convert BioCompute Object or domain to JSON string

Description

Convert BioCompute Object or domain to JSON string

Usage

convert_json(x, pretty = TRUE, auto_unbox = TRUE, na = "string", ...)

Arguments

x

BioCompute Object or domain

pretty

Prettify the JSON string? Default is TRUE.

auto_unbox

Unbox all atomic vectors of length 1? Default is TRUE.

na

How to represent NA values: must be "null" or "string". Default is "string".

...

Additional parameters for toJSON.

Value

JSON string of the BioCompute Object

Examples

compose_description() %>% convert_json()
generate_example("minimal") %>% convert_json()

Convert BioCompute Object or domain to YAML string

Description

Convert BioCompute Object or domain to YAML string

Usage

convert_yaml(x, ...)

Arguments

x

BioCompute Object or domain

...

Additional parameters for as.yaml.

Value

YAML string of the BioCompute Object

Examples

compose_description() %>%
  convert_yaml() %>%
  cat()
generate_example("minimal") %>%
  convert_yaml() %>%
  cat()

Export BioCompute Object as HTML

Description

Export BioCompute Object as HTML

Usage

export_html(x, file, wrap = FALSE, linewidth = 80, ...)

Arguments

x

BioCompute Object JSON string from convert_json

file

HTML output file path

wrap

Should the long lines be wrapped?

linewidth

Maximum linewidth when wrap is TRUE.

...

Additional parameters for render.

Value

Path to the output file

Examples

## Not run: 
file_html <- tempfile(fileext = ".html")
generate_example("HCV1a") %>%
  convert_json() %>%
  export_html(file_html)

## End(Not run)

Export BioCompute Object as JSON

Description

Export BioCompute Object as JSON

Usage

export_json(x, file)

Arguments

x

BioCompute Object JSON string from convert_json

file

JSON file path

Value

Path to the output file

Examples

file_json <- tempfile(fileext = ".json")
generate_example("HCV1a") %>%
  convert_json() %>%
  export_json(file_json)
cat(paste(readLines(file_json), collapse = "\n"))

Export BioCompute Object as PDF

Description

Export BioCompute Object as PDF

Usage

export_pdf(x, file, wrap = FALSE, linewidth = 80, ...)

Arguments

x

BioCompute Object JSON string from convert_json

file

PDF output file path

wrap

Should the long lines be wrapped?

linewidth

Maximum linewidth when wrap is TRUE.

...

Additional parameters for render.

Value

Path to the output file

Examples

## Not run: 
file_pdf <- tempfile(fileext = ".pdf")
generate_example("HCV1a") %>%
  convert_json() %>%
  export_pdf(file_pdf)

## End(Not run)

Export BioCompute Object to Seven Bridges Platforms

Description

Export BioCompute Object to Seven Bridges Platforms

Usage

export_sevenbridges(
  file,
  name = NULL,
  project = NULL,
  token = NULL,
  base_url = "https://api.sbgenomics.com/v2/",
  overwrite = TRUE
)

Arguments

file

Path to the BCO file.

name

Name of the BCO file to create on the platform. Defaults to the name of the input file.

project

Project to upload (export) the BCO file to. Format: "username/project".

token

API auth token for the platform. Generate the token from the platform's Developer Dashboard.

base_url

API base URL. Get the base URL from the platform's Developer Dashboard.

overwrite

If TRUE, will overwrite the existing BCO file with the same name in that project (if any). If FALSE, will not overwrite.

Value

Response of the file upload request

Examples

## Not run: 
file_json <- tempfile(fileext = ".json")
generate_example("HCV1a") %>%
  convert_json() %>%
  export_json(file_json)

try(
  export_sevenbridges(
    file_json,
    project = "rosalind_franklin/project_name",
    token = "your_api_auth_token",
    base_url = "https://cgc-api.sbgenomics.com/v2/"
  )
)

## End(Not run)

Export BioCompute Object as Word document

Description

Export BioCompute Object as Word document

Usage

export_word(x, file, wrap = FALSE, linewidth = 80, ...)

Arguments

x

BioCompute Object JSON string from convert_json

file

Word (docx) output file path

wrap

Should the long lines be wrapped?

linewidth

Maximum linewidth when wrap is TRUE.

...

Additional parameters for render.

Value

Path to the output file

Examples

## Not run: 
file_docx <- tempfile(fileext = ".docx")
generate_example("HCV1a") %>%
  convert_json() %>%
  export_word(file_docx)

## End(Not run)

Generate example BioCompute Objects

Description

Generate example BioCompute Objects

Usage

generate_example(type = c("minimal", "HCV1a"))

Arguments

type

Example type. Default is "minimal".

Value

Example BioCompute Object

Examples

generate_example("minimal") %>% convert_json()

Generate ID for the BioCompute Object

Description

Generate ID for the BioCompute Object

Usage

generate_id(platform = c("sevenbridges"))

Arguments

platform

Platform. Default is "sevenbridges".

Value

BioCompute Object ID

Examples

generate_id()

Is this a BCO object?

Description

Is this a BCO object?

Usage

is_bco(x)

Arguments

x

any object

Value

Logical. TRUE if it is a BCO object, FALSE if not.

Examples

generate_example("minimal") %>% is_bco()

Is this a domain object?

Description

Is this a domain object?

Usage

is_domain(x)

Arguments

x

any object

Value

Logical. TRUE if it is a domain object, FALSE if not.

Examples

is_domain(compose_description())

Parse Biocompute Object From JSON File to R Object

Description

Parse Biocompute Object From JSON File to R Object

Usage

read_bco(x, ...)

Arguments

x

BioCompute Object .json file

...

Additional parameters for fromJSON.

Value

A list of class bco

Examples

bco <- tempfile(fileext = ".json")
bco <- generate_example("HCV1a") %>%
  convert_json() %>%
  export_json(bco)
bco %>% read_bco()

BioCompute Objects checksum validator (v1.4.2)

Description

BioCompute Objects checksum validator (v1.4.2)

Usage

validate_checksum_v1.4.2(file)

validate_checksum(file)

Arguments

file

Path to the BCO JSON file

Value

Logical. TRUE if the checksum matched, FALSE if not.

Note

An SHA-256 checksum is calculated and stored in the top level fields when a BioCompute Object is created. In reality, due to the delicate differences in how the data in JSON is represented, parsed, and handled in different languages, there could be false positives in the validation results.

Examples

bco <- tempfile(fileext = ".json")
generate_example("HCV1a") %>%
  convert_json() %>%
  export_json(bco)
bco %>% validate_checksum()

BioCompute Objects schema validator (v1.4.2)

Description

BioCompute Objects schema validator (v1.4.2)

Usage

validate_schema_v1.4.2(file)

validate_schema(file)

Arguments

file

Path to the BCO JSON file

Value

None

Note

JSON schema validators for BCO domains and complete BCO based on jsonvalidate. Refer to the BioCompute Objects Schema for specific JSON schemas.

Examples

bco <- tempfile(fileext = ".json")
generate_example("HCV1a") %>%
  convert_json() %>%
  export_json(bco)
bco %>% validate_schema()

BioCompute Object specification versions

Description

BioCompute Object specification versions

Usage

versions()

Value

List of current and all available BioCompute Object specification versions supported by the package.

Examples

versions()