Package 'cbpManager' reference manual

Title:	Generate, manage, and edit data and metadata files suitable for the import in cBioPortal for Cancer Genomics
Description:	This R package provides an R Shiny application that enables the user to generate, manage, and edit data and metadata files suitable for the import in cBioPortal for Cancer Genomics. Create cancer studies and edit its metadata. Upload mutation data of a patient that will be concatenated to the data_mutation_extended.txt file of the study. Create and edit clinical patient data, sample data, and timeline data. Create custom timeline tracks for patients.
Authors:	Arsenij Ustjanzew [aut, cre, cph] , Federico Marini [aut]
Maintainer:	Arsenij Ustjanzew <[email protected]>
License:	AGPL-3 + file LICENSE
Version:	1.13.0
Built:	2024-09-10 05:41:09 UTC
Source:	https://github.com/bioc/cbpManager

Server logic of module for adding a column

Description

Server logic of module for adding a column

Usage

addColumn_Server(input, output, session, data)
addColumn_Server(input, output, session, data)

Arguments

`input`	Shiny input
`output`	Shiny output
`session`	Shiny session
`data`	source data as data.frame

Value

reactive data.frame of modified source data

UI elements of module for adding a column

Description

UI elements of module for adding a column

Usage

addColumn_UI(id, label = "Add column")
addColumn_UI(id, label = "Add column")

Arguments

`id`	module id
`label`	label of the button

Value

UI module

Server logic of module for adding a row

Description

Server logic of module for adding a row

Usage

addRow_Server(
  input,
  output,
  session,
  data,
  patient_ids = NULL,
  dates_first_diagnosis = NULL,
  mode = c("timeline", "timepoint")
)
addRow_Server(
  input,
  output,
  session,
  data,
  patient_ids = NULL,
  dates_first_diagnosis = NULL,
  mode = c("timeline", "timepoint")
)

Arguments

`input`	Shiny input
`output`	Shiny output
`session`	Shiny session
`data`	source data as data.frame
`patient_ids`	reactive vector of existing patient IDs
`dates_first_diagnosis`	data.frame with dates of the first diagnosis and patient IDs
`mode`	Mode of the timeline data. Controls which columns are displayed.

Value

reactive data.frame of modified source data

UI elements of module for adding a row

Description

UI elements of module for adding a row

Usage

addRow_UI(id, label = "Add")
addRow_UI(id, label = "Add")

Arguments

`id`	module id
`label`	label of the button

Value

UI module

Server logic of Resource tab module for adding a row

Description

Server logic of Resource tab module for adding a row

Usage

addRowRc_Server(
  input,
  output,
  session,
  data,
  patient_ids = NULL,
  sample_ids = NULL,
  resource_ids = NULL,
  resource_type = c("definition", "sample", "patient", "study")
)
addRowRc_Server(
  input,
  output,
  session,
  data,
  patient_ids = NULL,
  sample_ids = NULL,
  resource_ids = NULL,
  resource_type = c("definition", "sample", "patient", "study")
)

Arguments

`input`	Shiny input
`output`	Shiny output
`session`	Shiny session
`data`	Source data as data.frame
`patient_ids`	Reactive vector of existing patient IDs
`sample_ids`	Reactive data.frame of existing patient IDs and sample IDs
`resource_ids`	Reactive data.frame of data_resource_definition
`resource_type`	The type of the resource. Can be "definition", "sample", "patient", "study"

Value

reactive data.frame of modified source data

UI elements of Resource tab module for adding a row

Description

UI elements of Resource tab module for adding a row

Usage

addRowRc_UI(id, label = "Add")
addRowRc_UI(id, label = "Add")

Arguments

`id`	module id
`label`	label of the button

Value

UI module

Convert the cBioPortal sample- and patient-data file format into a data.frame

Description

This function takes a file object (from read.table), removes the # symbol, sets the 5th row as the column names of the data.frame and removes the rows containing the priority, data type and column name. use read.table as follows: read.table(file, sep='\t', colClasses = 'character', comment.char = '')

Usage

cBioPortalToDataFrame(data)
cBioPortalToDataFrame(data)

Arguments

data

The data.frame of a cBioPortal sample/patient data file

Value

data.frame

Examples

df <- data.frame(
        V1=c("#attr_1", "#attribute 1", "#STRING", "#1", "ATTRIBUTE_1", "value_1"), 
        V2=c("attr_2", "attribute 2", "STRING", "1", "ATTRIBUTE_2", "value_2")
    )
cbpManager:::cBioPortalToDataFrame(df)

df <- data.frame(
        V1=c("#attr_1", "#attribute 1", "#STRING", "#1", "ATTRIBUTE_1", "value_1"), 
        V2=c("attr_2", "attribute 2", "STRING", "1", "ATTRIBUTE_2", "value_2")
    )
cbpManager:::cBioPortalToDataFrame(df)

Launch cbpManager

Description

Launch the cbpManager Shiny application.

Usage

cbpManager(studyDir = NULL, logDir = NULL, returnAppObj = FALSE, ...)
cbpManager(studyDir = NULL, logDir = NULL, returnAppObj = FALSE, ...)

Arguments

`studyDir`	Path to study folder containing studies of cBioPortal.
`logDir`	Path where a logfile should be saved. If NULL, logs are not stored
`returnAppObj`	Logical value, whether to return the app object if set to TRUE. Default behavior: directly runs the app (FALSE)
`...`	Further parameters that are used by `shiny::runApp`, e.g. `host` or `port`.

Value

shiny application object

Examples

if (interactive()) {
  cbpManager()
}
if (interactive()) {
  cbpManager()
}

cbpManager

Description

'cbpManager' is an R package that provides an interactive Shiny-based graphical user interface for...

Author(s)

Arsenij Ustjanzew [email protected]

Check the input of dates

Description

Check the input of dates

Usage

check_input_dates(diagnosisDate, startDate = NULL, endDate = NULL)
check_input_dates(diagnosisDate, startDate = NULL, endDate = NULL)

Arguments

`diagnosisDate`	date of first diagnosis
`startDate`	start date of timeline event
`endDate`	end date of timeline event

Value

Returns a number indicating the warning

Examples

cbpManager:::check_input_dates(
    diagnosisDate = "2020-01-01", 
    startDate = "2020-02-01", 
    endDate = "2020-03-01"
) #returns 0
cbpManager:::check_input_dates(
    diagnosisDate = "2020-01-01", 
    startDate = "2019-02-01"
) #returns 2
cbpManager:::check_input_dates(
    diagnosisDate = "2020-01-01", 
    endDate = "2019-02-01"
) #returns 2
cbpManager:::check_input_dates(
    diagnosisDate = "2020-01-01", 
    startDate = "2020-03-01", 
    endDate = "2020-02-01"
) #returns 1

cbpManager:::check_input_dates(
    diagnosisDate = "2020-01-01", 
    startDate = "2020-02-01", 
    endDate = "2020-03-01"
) #returns 0
cbpManager:::check_input_dates(
    diagnosisDate = "2020-01-01", 
    startDate = "2019-02-01"
) #returns 2
cbpManager:::check_input_dates(
    diagnosisDate = "2020-01-01", 
    endDate = "2019-02-01"
) #returns 2
cbpManager:::check_input_dates(
    diagnosisDate = "2020-01-01", 
    startDate = "2020-03-01", 
    endDate = "2020-02-01"
) #returns 1

Convert the data.frame to the appropriate file format for cBioPortal

Description

Convert the data.frame to the appropriate file format for cBioPortal

Usage

convertDataFrame(df)
convertDataFrame(df)

Arguments

`df`	data.frame

Value

Data.frame formated for the cBioPortal file format

Examples

cbpManager:::convertDataFrame(
    data.frame(
        ATTRIBUTE1=c("attr_1", "attribute 1", "STRING", "value_a1"), 
        ATTRIBUTE2=c("attr_2", "attribute 2", "STRING", "value_b1")
    )
)

cbpManager:::convertDataFrame(
    data.frame(
        ATTRIBUTE1=c("attr_1", "attribute 1", "STRING", "value_a1"), 
        ATTRIBUTE2=c("attr_2", "attribute 2", "STRING", "value_b1")
    )
)

Sanitize names

Description

This function takes a character string, replaces spaces by underscores and runs make.names.

Usage

create_name(x, toupper = TRUE)
create_name(x, toupper = TRUE)

Arguments

`x`	A character string.
`toupper`	If TRUE, the name wil be upper-case; if FALSE, the name will be lower-case.

Value

A sanitized string.

Examples

cbpManager:::create_name("Study name 1") #returns "STUDY_NAME_1"
cbpManager:::create_name("FANCY;name", toupper = FALSE) #returns "fancy.name"

cbpManager:::create_name("Study name 1") #returns "STUDY_NAME_1"
cbpManager:::create_name("FANCY;name", toupper = FALSE) #returns "fancy.name"

Server logic of module for deleting a column

Description

Server logic of module for deleting a column

Usage

deleteColumn_Server(input, output, session, data, exclude)
deleteColumn_Server(input, output, session, data, exclude)

Arguments

`input`	Shiny input
`output`	Shiny output
`session`	Shiny session
`data`	source data as data.frame
`exclude`	column names that shoud be excluded from deletion

Value

reactive data.frame of modified source data

UI elements of module for deleting a column

Description

UI elements of module for deleting a column

Usage

deleteColumn_UI(id, label = "Delete column(s)")
deleteColumn_UI(id, label = "Delete column(s)")

Arguments

`id`	module id
`label`	label of the button

Value

UI module

Server logic of module for removing a row

Description

Server logic of module for removing a row

Usage

deleteRow_Server(input, output, session, data, selected_row)
deleteRow_Server(input, output, session, data, selected_row)

Arguments

`input`	Shiny input
`output`	Shiny output
`session`	Shiny session
`data`	source data as data.frame
`selected_row`	Index of the selected row from the table

Value

reactive data.frame of modified source data

UI elements of module for removing a row

Description

UI elements of module for removing a row

Usage

deleteRow_UI(id, label = "Delete")
deleteRow_UI(id, label = "Delete")

Arguments

`id`	module id
`label`	label of the button

Value

UI module

Server logic of Resource tab module for deleting a row

Description

Server logic of Resource tab module for deleting a row

Usage

deleteRowRc_Server(
  input,
  output,
  session,
  data,
  selected_row,
  mode = "default",
  sample_data = NULL,
  patient_data = NULL,
  study_data = NULL
)
deleteRowRc_Server(
  input,
  output,
  session,
  data,
  selected_row,
  mode = "default",
  sample_data = NULL,
  patient_data = NULL,
  study_data = NULL
)

Arguments

`input`	Shiny input
`output`	Shiny output
`session`	Shiny session
`data`	Source data as data.frame
`selected_row`	Index of the selected row from the table
`mode`	If 'recursive' the resources bind to the resource definition will be deleted.
`sample_data`	Data of the resource from type 'sample'
`patient_data`	Data of the resource from type 'patient'
`study_data`	Data of the resource from type 'study'

Value

reactive data.frame of modified source data

UI elements of module for removing a row

Description

UI elements of module for removing a row

Usage

deleteRowRc_UI(id, label = "Delete")
deleteRowRc_UI(id, label = "Delete")

Arguments

`id`	Module id
`label`	Label of the button

Value

UI module

Server logic of module for editing a row

Description

Server logic of module for editing a row

Usage

editRow_Server(
  input,
  output,
  session,
  data,
  patient_ids = NULL,
  dates_first_diagnosis = NULL,
  selected_row = NULL,
  mode = c("timeline", "timepoint")
)
editRow_Server(
  input,
  output,
  session,
  data,
  patient_ids = NULL,
  dates_first_diagnosis = NULL,
  selected_row = NULL,
  mode = c("timeline", "timepoint")
)

Arguments

`input`	Shiny input
`output`	Shiny output
`session`	Shiny session
`data`	source data as data.frame
`patient_ids`	reactive vector of existing patient IDs
`dates_first_diagnosis`	data.frame with dates of the first diagnosis and patient IDs
`selected_row`	the index of the selected row
`mode`	Mode of the timeline data. Controls which columns are displayed.

Value

reactive data.frame of modified source data

UI elements of module for editing a row

Description

UI elements of module for editing a row

Usage

editRow_UI(id, label = "Edit")
editRow_UI(id, label = "Edit")

Arguments

`id`	module id
`label`	label of the button

Value

UI module

Server logic of Resource tab module for editing a row

Description

Server logic of Resource tab module for editing a row

Usage

editRowRc_Server(
  input,
  output,
  session,
  data,
  patient_ids = NULL,
  sample_ids = NULL,
  resource_ids = NULL,
  selected_row = NULL,
  resource_type = c("definition", "sample", "patient", "study")
)
editRowRc_Server(
  input,
  output,
  session,
  data,
  patient_ids = NULL,
  sample_ids = NULL,
  resource_ids = NULL,
  selected_row = NULL,
  resource_type = c("definition", "sample", "patient", "study")
)

Arguments

`input`	Shiny input
`output`	Shiny output
`session`	Shiny session
`data`	Source data as data.frame
`patient_ids`	Reactive vector of existing patient IDs
`sample_ids`	Reactive data.frame of existing patient IDs and sample IDs
`resource_ids`	Reactive data.frame of data_resource_definition
`selected_row`	Index of the selected row
`resource_type`	The type of the resource. Can be "definition", "sample", "patient", "study"

Value

reactive data.frame of modified source data

UI elements of module for editing a row

Description

UI elements of module for editing a row

Usage

editRowRc_UI(id, label = "Edit")
editRowRc_UI(id, label = "Edit")

Arguments

`id`	Module id
`label`	Label of the button

Value

UI module

Add empty column to a data.frame, if column does not exist in the data.frame

Description

Add empty column to a data.frame, if column does not exist in the data.frame

Usage

fncols(data, cname)
fncols(data, cname)

Arguments

`data`	data.frame
`cname`	column name

Value

data.frame

Examples

cbpManager:::fncols(data.frame(a=c(1,2,3), b=c(4,5,6)), "new")

cbpManager:::fncols(data.frame(a=c(1,2,3), b=c(4,5,6)), "new")

Create shiny UI-widget for specific columns of oncotree entries

Description

Create shiny UI-widget for specific columns of oncotree entries

Usage

generateOncotreeUIwidgets(
  colname,
  mode = c("add", "edit"),
  tab = c("Patient", "Sample")
)
generateOncotreeUIwidgets(
  colname,
  mode = c("add", "edit"),
  tab = c("Patient", "Sample")
)

Arguments

`colname`	column name
`mode`	determines the inputId prefix of the UI-widget
`tab`	"Patient", "Sample" - The used tab; sets the html id prefix of the input

Value

A oncotree specific shiny UI-widget

Examples

oncotree <- jsonlite::fromJSON(system.file("extdata", "oncotree.json", package = "cbpManager"))
cancer_type <- unique(oncotree$mainType[which(!is.na(oncotree$mainType))])
cbpManager:::generateOncotreeUIwidgets("CANCER_TYPE", "add")

oncotree <- jsonlite::fromJSON(system.file("extdata", "oncotree.json", package = "cbpManager"))
cancer_type <- unique(oncotree$mainType[which(!is.na(oncotree$mainType))])
cbpManager:::generateOncotreeUIwidgets("CANCER_TYPE", "add")

Generate UI input widget

Description

Generate UI input widget

Usage

generateUIwidgets(
  colname,
  mode = c("add", "edit"),
  tab = c("Patient", "Sample", "Mutation"),
  data = NULL,
  selected_row = NULL,
  patientIDs = NULL,
  sampleIDs = NULL
)
generateUIwidgets(
  colname,
  mode = c("add", "edit"),
  tab = c("Patient", "Sample", "Mutation"),
  data = NULL,
  selected_row = NULL,
  patientIDs = NULL,
  sampleIDs = NULL
)

Arguments

`colname`	A character string - the name of the column, that will be the label of the input
`mode`	"add" or "edit" - whether to use existing values or not
`tab`	"Patient", "Sample" - The used tab; sets the html id prefix of the input
`data`	A data.frame.
`selected_row`	A number indicating the row number of the selected row in the data.frame.
`patientIDs`	Vector of patient IDs used for drop down menu of the PATIENT_ID column

Value

A sanitized string.

Examples

cbpManager:::generateUIwidgets(colname = "attribute", mode = "add", tab = "Patient")

cbpManager:::generateUIwidgets(colname = "attribute", mode = "add", tab = "Patient")

Get Sample IDs associated with Patient IDs from the data_clinical_sample.txt file

Description

Get Sample IDs associated with Patient IDs from the data_clinical_sample.txt file

Usage

getSampleIDs(file_path, patIDs)
getSampleIDs(file_path, patIDs)

Arguments

`file_path`	A character string.
`patIDs`	A character string.

Value

vector with Sample IDs

Examples

cbpManager:::getSampleIDs(
    system.file("study/testpatient/data_clinical_sample.txt", package = "cbpManager"), 
    patIDs = "Testpatient")

cbpManager:::getSampleIDs(
    system.file("study/testpatient/data_clinical_sample.txt", package = "cbpManager"), 
    patIDs = "Testpatient")

Import patient data into current study data.frames

Description

Import patient data into current study data.frames

Usage

importPatientData(
  mode = c("patient", "sample", "mutations", "timelines"),
  file_name,
  file_path,
  patIDs,
  data,
  associatedSampleIDs = NULL
)
importPatientData(
  mode = c("patient", "sample", "mutations", "timelines"),
  file_name,
  file_path,
  patIDs,
  data,
  associatedSampleIDs = NULL
)

Arguments

`mode`	Defines the type of imported data
`file_name`	Filename of source data
`file_path`	Filepath with filename of source data
`patIDs`	PATIENT_IDs of patients that should be imported
`data`	Source data, to be subsetted according to patIDs
`associatedSampleIDs`	The sample IDs associated to the patIDs

Value

data.frame

Check if input is in the appropriate date format

Description

Check if input is in the appropriate date format

Usage

IsDate(mydate, date.format = "%Y-%m-%d")
IsDate(mydate, date.format = "%Y-%m-%d")

Arguments

`mydate`	date
`date.format`	string describig the date format

Value

boolean

Examples

cbpManager:::IsDate("2020-02-20")
cbpManager:::IsDate("20.01.2020", date.format = "%d.%m.%Y")

cbpManager:::IsDate("2020-02-20")
cbpManager:::IsDate("20.01.2020", date.format = "%d.%m.%Y")

Server logic of module for saving the resource data

Description

Server logic of module for saving the resource data

Usage

saveResource_Server(
  input,
  output,
  session,
  data,
  study_id,
  data_filename,
  meta_filename,
  resource_type = c("SAMPLE", "DEFINITION", "PATIENT", "STUDY")
)
saveResource_Server(
  input,
  output,
  session,
  data,
  study_id,
  data_filename,
  meta_filename,
  resource_type = c("SAMPLE", "DEFINITION", "PATIENT", "STUDY")
)

Arguments

`input`	Shiny input
`output`	Shiny output
`session`	Shiny session
`data`	Source data as data.frame
`study_id`	The current study ID
`data_filename`	File name of the data file
`meta_filename`	file name of the meta file
`resource_type`	The type of the resource. Can be "definition", "sample", "patient", "study"

Value

boolean value; TRUE if function was used.

UI elements of module for saving the resource data

Description

UI elements of module for saving the resource data

Usage

saveResource_UI(id, label = "Save")
saveResource_UI(id, label = "Save")

Arguments

`id`	module id
`label`	label of the button

Value

UI module

Server logic of module for saving the source data

Description

Server logic of module for saving the source data

Usage

saveTimeline_Server(input, output, session, data, study_id)
saveTimeline_Server(input, output, session, data, study_id)

Arguments

`input`	Shiny input
`output`	Shiny output
`session`	Shiny session
`data`	source data as data.frame
`study_id`	the current study ID

Value

boolean value; TRUE if function was used.

UI elements of module for saving the data

Description

UI elements of module for saving the data

Usage

saveTimeline_UI(id, label = "Save")
saveTimeline_UI(id, label = "Save")

Arguments

`id`	module id
`label`	label of the button

Value

UI module

Install conda environment with basilisk before launching the app

Description

Install conda environment with basilisk before launching the app

Usage

setupConda_cbpManager()
setupConda_cbpManager()

Value

Nothing to return

Examples

## Not run: 
setupConda_cbpManager()

## End(Not run)

## Not run: 
setupConda_cbpManager()

## End(Not run)

Shiny app server function

Description

Shiny app server function

Usage

shinyAppServer(input, output, session)
shinyAppServer(input, output, session)

Arguments

`input`	provided by shiny
`output`	provided by shiny
`session`	provided by shiny

Value

nothing to return

Shiny app server object create the shiny application user interface

Description

Shiny app server object create the shiny application user interface

Usage

shinyAppUI
shinyAppUI

Format

An object of class shiny.tag of length 3.

Updates UI-widgets for specific columns of oncotree entries

Description

Updates UI-widgets for specific columns of oncotree entries

Usage

updateOncotreeUIwidgets(
  session,
  row_last_clicked,
  mode = c("add", "edit"),
  tab = c("Patient", "Sample")
)
updateOncotreeUIwidgets(
  session,
  row_last_clicked,
  mode = c("add", "edit"),
  tab = c("Patient", "Sample")
)

Arguments

`session`	Shiny session
`row_last_clicked`	the index of the row last clicked in the oncotree_table
`mode`	determines the inputId prefix of the UI-widget
`tab`	"Patient", "Sample" - The used tab; sets the html id pr

Value

nothing to return

Validate resource_definition input

Description

Validate resource_definition input

Usage

validateResourceDefinition(values, resourceDf, mode = "add")
validateResourceDefinition(values, resourceDf, mode = "add")

Arguments

`values`	List of input values
`resourceDf`	data.frame of data_resource_definition
`mode`	The mode of the function ('add' or 'edit')

Value

boolean

Validate resource_patient input

Description

Validate resource_patient input

Usage

validateResourcePatient(values)
validateResourcePatient(values)

Arguments

values

List of input values

Value

boolean

Validate resource_sample input

Description

Validate resource_sample input

Usage

validateResourceSample(values)
validateResourceSample(values)

Arguments

values

List of input values

Value

boolean

Validate resource_study input

Description

Validate resource_study input

Usage

validateResourceStudy(values)
validateResourceStudy(values)

Arguments

values

List of input values

Value

boolean

Validation Dependencies

Description

Vector defining a set of Python dependencies and versions required to operate with the validation scripts for cBioPortal

Usage

.validation_dependencies
.validation_dependencies

Format

A character vector containing the pinned versions of all Python packages on which the import validation depends.

Write a line to a logfile containing the date, time, username (from Shinyproxy), and the name of the modified file.

Description

Write a line to a logfile containing the date, time, username (from Shinyproxy), and the name of the modified file.

Usage

writeLogfile(outdir, modified_file, log_filename = "cbpManager_logfile.txt")
writeLogfile(outdir, modified_file, log_filename = "cbpManager_logfile.txt")

Arguments

`outdir`	directory, where the logfile should be saved
`modified_file`	Name of the modified file
`log_filename`	Name of the logfile

Value

Nothing to return

Examples

cbpManager:::writeLogfile(tempdir(), "data_clinical_patient.txt")

cbpManager:::writeLogfile(tempdir(), "data_clinical_patient.txt")

Package 'cbpManager'

Help Index

Server logic of module for adding a column

Description

Usage

Arguments

Value

UI elements of module for adding a column

Description

Usage

Arguments

Value

Server logic of module for adding a row

Description

Usage

Arguments

Value

UI elements of module for adding a row

Description

Usage

Arguments

Value

Server logic of Resource tab module for adding a row

Description

Usage

Arguments

Value

UI elements of Resource tab module for adding a row

Description

Usage

Arguments

Value

Convert the cBioPortal sample- and patient-data file format into a data.frame

Description

Usage

Arguments

Value

Examples

Launch cbpManager

Description

Usage

Arguments

Value

Examples

cbpManager

Description

Author(s)

Check the input of dates

Description

Usage

Arguments

Value

Examples

Convert the data.frame to the appropriate file format for cBioPortal

Description

Usage

Arguments

Value

Examples

Sanitize names

Description

Usage

Arguments

Value

Examples

Server logic of module for deleting a column

Description

Usage

Arguments

Value

UI elements of module for deleting a column

Description

Usage

Arguments

Value

Server logic of module for removing a row

Description

Usage

Arguments

Value