Package 'gDRimport'

Title: Package for handling the import of dose-response data
Description: The package is a part of the gDR suite. It helps to prepare raw drug response data for downstream processing. It mainly contains helper functions for importing/loading/validating dose-response data provided in different file formats.
Authors: Arkadiusz Gladki [aut, cre] (ORCID: <https://orcid.org/0000-0002-7059-6378>), Bartosz Czech [aut] (ORCID: <https://orcid.org/0000-0002-9908-3007>), Marc Hafner [aut] (ORCID: <https://orcid.org/0000-0003-1337-7598>), Sergiu Mocanu [aut], Dariusz Scigocki [aut], Allison Vuong [aut], Luca Gerosa [aut] (ORCID: <https://orcid.org/0000-0001-6805-9410>), Janina Smola [aut] (ORCID: <https://orcid.org/0009-0007-4347-7748>)
Maintainer: Arkadiusz Gladki <[email protected]>
License: Artistic-2.0
Version: 1.11.8
Built: 2026-10-09 09:22:46 UTC
Source: https://github.com/bioc/gDRimport

Help Index

check_metadata_names

Description

Check whether all metadata names are correct

Usage

check_metadata_names(col_df, df_name = "", df_type = NULL)

Arguments

col_df

a character with colnames of df
df_name

a name of data.table ("" by default)
df_type

a type of a data.table (NULL by default)

Value

a charvec with corrected colnames of df

Examples

td <- get_test_data()
 m_file <- manifest_path(td)
 m_data <- read_excel_to_dt(m_file)
 result <- check_metadata_names(col_df = colnames(m_data))

Load, convert and process the level 5 PRISM data into a gDR input

Description

Load, convert and process the level 5 PRISM data into a gDR input

Usage

convert_LEVEL5_prism_to_gDR_input(
  prism_data_path,
  meta_data_path,
  readout_min = 1.03
)

Arguments

prism_data_path

path to PRISM LEVEL5 csv file with data
meta_data_path

path to metadata file describing all cancer models/cell lines which are referenced by a dataset contained within the DepMap portal
readout_min

minimum ReadoutValue

Value

data.table object with input data for gDR pipeline

Examples

prism_data <- system.file("testdata/prism_sa.csv", package = "gDRimport")
 prism_meta <- system.file("testdata/prism_model.csv", package = "gDRimport")
 convert_LEVEL5_prism_to_gDR_input(prism_data, prism_meta)

Load, convert and process the level 6 PRISM data into a gDR input

Description

Load, convert and process the level 6 PRISM data into a gDR input

Usage

convert_LEVEL6_prism_to_gDR_input(
  prism_data_path,
  cell_line_data_path,
  treatment_data_path,
  meta_data_path,
  readout_min = 1.03
)

Arguments

prism_data_path

path to PRISM LEVEL6 csv file with collapsed log fold change data
cell_line_data_path

path to cell line info data
treatment_data_path

path to collapsed treatment info data
meta_data_path

path to metadata file describing all cancer models/cell lines which are referenced by a dataset contained within the DepMap portal
readout_min

minimum ReadoutValue

Value

data.table object with input data for gDR pipeline

Examples

prism_data_path <- system.file("testdata/prism_collapsed_LOGFC.csv", package = "gDRimport")
 cell_line_data_path <- system.file("testdata/prism_cell_lines.csv", package = "gDRimport")
 treatment_data_path <- system.file("testdata/prism_treatment.csv", package = "gDRimport")
 prism_meta <- system.file("testdata/prism_model.csv", package = "gDRimport")
 convert_LEVEL6_prism_to_gDR_input(prism_data_path, cell_line_data_path, treatment_data_path, prism_meta)

Convert MultiAssayExperiment to TreatmentResponseExperiment

Description

This function converts a MultiAssayExperiment generated by gDR into a TreatmentResponseExperiment for use in the PharmacoGx package. The resulting PharmacoSet can be used for pharmacogenomic analysis of drug response.

Usage

convert_MAE_to_PSet(mae, pset_name)

Arguments

mae

A MultiAssayExperiment object generated by gDR.
pset_name

A character string specifying the name of the resulting PharmacoSet object.

Value

A PharmacoSet object.

Examples

# Convert a MultiAssayExperiment object to a PharmacoSet object
m <- 20
n <- 10
rnames <- LETTERS[1:m]
cnames <- letters[1:n]
ref_gr_value <-  matrix(runif(m * n), nrow = m, ncol = n, dimnames = list(rnames, cnames))
se <- SummarizedExperiment::SummarizedExperiment(assays = list(RefGRvalue = ref_gr_value),
                                                 rowData = S4Vectors::DataFrame(rnames),
                                                 colData = S4Vectors::DataFrame(cnames))
mae <- MultiAssayExperiment::MultiAssayExperiment(experiments = list("single-agent" = se))
convert_MAE_to_PSet(mae, "my_pset")

Convert a PharmacoSet to a data.table that is prepare for input into gDR pipeline

Description

Convert a PharmacoSet to a data.table that is prepare for input into gDR pipeline

Usage

convert_pset_to_df(pharmacoset, run_parallel = TRUE, workers = 2L)

Arguments

pharmacoset

PharmacoSet object
run_parallel

logical, TRUE (default) if to run functions in Parallel, FALSE to run in serial
workers

integer, number of workers defaults to 2L if run_parallel is TRUE

Value

data.table of PharmacoSet's dose response data with column names aligned with gDR standard

Author(s)

Jermiah Joseph – collaboration with BHKLab

Examples

pset <- suppressMessages(getPSet(
  "Tavor_2020",
  psetDir = system.file("extdata/pset", package = "gDRimport"),
  use_local_PSets_list = TRUE
))
dt <- convert_pset_to_df(pset)
gDRutils::reset_env_identifiers()

Detect format of results data

Description

Detect format of results data

Usage

detect_file_format(results_file)

Arguments

results_file

path to results data

Value

string of the detected file format

Examples

td2 <- get_test_Tecan_data()
detect_file_format(td2$r_files[1])

Fix typos using reference data

Description

Fix typos using reference data Evaluate given list of ids and try to update them

Usage

fix_typos_with_reference(
  data,
  ref,
  method = c("exact", "grepl", "adist"),
  fix_underscores = FALSE
)

Arguments

data

list of charvec(s) or charvec with data
ref

charvec with reference data
method

charvec type of the method to be used 'exact' is used to find identical entries from 'ref' in the data (after corrections and uppercase'ing) 'grepl' is used to find entries from 'ref' that might be somehow pre- or post- fixed
fix_underscores

logical flag fix the issues with underscores in data identfiers?

Value

list or charvec with corrected data

gDR Test Data object

Description

Object class gdr_test_data is build by function get_test_data()

Value

object class gdr_test_data with primary test data

Slots

manifest_path

character, path to manifest file

result_path

character, path(s) to results file

template_path

character, path(s) to data.table with template data

ref_m_df

character, data.table with manifest data

ref_r1_r2

character, path to reference file with raw data for treated & untreated

ref_r1

character, path to reference file with raw data for treated

ref_t1_t2

character, path to reference template file with treated & untreated data

ref_t1

character, path to reference template file with treated data

Get final results (as a data.table) from raw edited EnVision data.table

Description

Get final results (as a data.table) from raw edited EnVision data.table

Usage

get_df_from_raw_edited_EnVision_df(
  df,
  barcode_idx,
  barcode_col,
  n_row,
  n_col,
  fname,
  sheet_name,
  headers
)

Arguments

df

raw data.table
barcode_idx

numeric vector with barcode indices
barcode_col

column number for barcode data
n_row

number of rows
n_col

number of columns
fname

file name
sheet_name

name of the Excel sheet
headers

list with the headersa

Value

data.table derived from EnVision data

Get final results (as a data.table) from raw unedited EnVision data.table

Description

Get final results (as a data.table) from raw unedited EnVision data.table

Usage

get_df_from_raw_unedited_EnVision_df(df, n_row, n_col, barcode_col)

Arguments

df

raw data.table
n_row

number of rows
n_col

number of columns
barcode_col

column number for barcode data

Value

data.table derived from EnVision data

get exception data

Description

get exception data

Usage

get_exception_data(status_code = NULL)

Arguments

status_code

A numeric value

Value

A data.table row with exception data or all exceptions

Examples

get_exception_data(1)
get_exception_data()

Get names of the sheets expected in templates xlsx

Description

Get names of the sheets expected in templates xlsx

Usage

get_expected_template_sheets(type = c("all", "core", "optional"))

Arguments

type

charvec type of the sheets

Value

string with type of the sheets

get test D300 data

Description

get test D300 data

Usage

get_test_D300_data()

Value

list with with input data (manifest/template/result paths) and related reference data (qs2 file paths)

Examples

get_test_D300_data()

get primary test data

Description

get primary test data

Usage

get_test_data()

Value

object class "gdr_test_data" with with input data (manifest/template/result paths) and related reference data (qs2 file paths)

Examples

get_test_data()

get test EnVision data

Description

get test EnVision data

Usage

get_test_EnVision_data()

Value

list with with input data (manifest/template/result paths) and related reference data (.qs2 file paths)

Examples

get_test_EnVision_data()

get test Tecan data

Description

get test Tecan data

Usage

get_test_Tecan_data()

Value

list with with input data (manifest/template/result paths) and related reference data (qs2 file paths)

Examples

get_test_Tecan_data()

get test tsv data

Description

get test tsv data

Usage

get_test_tsv_data()

Value

list with with input data (manifest/template/result paths) and related reference data (.qs2 file paths)

Examples

get_test_tsv_data()

Get PharmacoSet

Description

Get PharmacoSet

Usage

getPSet(
  pset_name,
  psetDir = getwd(),
  canonical = FALSE,
  timeout = 600,
  use_local_PSets_list = FALSE
)

Arguments

pset_name

string with the name of the PharmacoSet
psetDir

string with the temporary directory for the PharmacoSet
canonical

logical flag indicating if the PSet canonical
timeout

maximum number of seconds allowed for PSet download
use_local_PSets_list

logical flag if PSets list should be used from local. If FALSE PSets list will be taken from web.

Value

PharmacoSet object

Examples

suppressMessages(getPSet(
  "Tavor_2020",
  psetDir = system.file("extdata/pset", package = "gDRimport"),
  use_local_PSets_list = TRUE
))

Import D300

Description

This functions takes a D300 file and generates corresponding template files

Usage

import_D300(D300_file, destination_path, metadata_file = NULL, day0 = FALSE)

Arguments

D300_file

character, file path to D300 file
destination_path

character, path to folder where template files will be generated
metadata_file

character, file path to file with mapping from D300 names to Gnumbers. Defaults to NULL.
day0

logical, if TRUE, creates a template file for Day 0 data filled with vehicles in addition to the standard plates. Defaults to FALSE.

Details

For example, wells treated with 2 drugs in combination will result in 4 sheets per plate.

  • Sheet 1: Drug 1

  • Sheet 2: Conc of Drug 1

  • Sheet 3: Drug 2

  • Sheet 4: Conc of Drug 2

Value

Create one Excel file per plate. Each sheet in each plate file describes the drugs and corrresponding concentrations of what was tested in each well.

Examples

td3 <- get_test_D300_data()[["f_96w"]]
o_path <- file.path(tempdir(), "td3")
dir.create(o_path)
import_D300(td3$d300, o_path, td3$Gnum)
list.files(o_path)
unlink(o_path, recursive = TRUE)

is_readable_v Check if all paths in vector are readable

Description

is_readable_v Check if all paths in vector are readable

Usage

is_readable_v(paths)

Arguments

paths

a character with path(s)

Value

NULL invisibly.

Examples

td2 <- get_test_Tecan_data()
is_readable_v(td2$r_files)

Load data

Description

This functions loads and checks the data file(s)

Usage

load_data(
  manifest_file,
  df_template_files,
  results_file,
  instrument = "EnVision"
)

Arguments

manifest_file

character, file path(s) to manifest(s)
df_template_files

data.table, with datapaths and names of results file(s) or character with file path of templates file(s)
results_file

data.table, with datapaths and names of results file(s) or character with file path of results file(s)
instrument

character

Value

a list with three data.tables for manifest/treatment and results

Examples

td <- get_test_data()
 l_tbl <- load_data(manifest_path(td), template_path(td), result_path(td))

Load long table

Description

Loads a long/tidy data.table from a delimited text file (CSV/TSV) and checks that it contains the columns required by the gDR pipeline. This offers an input path that does not rely on GeneDataScreeneR: the data can come from a custom export or be provided directly by the user in tabular form, matching the shape of the data_imported object used downstream.

Usage

load_long_table(long_table_file)

Arguments

long_table_file

character, path to a single CSV/TSV file with the long table. The field separator is detected automatically.

Details

Required columns follow the current gDR identifiers: Gnumber, clid, Duration and Concentration. The readout column is the fixed header ReadoutValue: there is no "readout" identifier in gDRutils, so this name is not customisable via get_env_identifiers(), matching how ReadoutValue is used across the rest of gDRimport. Combination data may add Gnumber_2 and Concentration_2. Duration, Concentration and ReadoutValue must be numeric.

Value

a data.table with the validated long table

Examples

path <- tempfile(fileext = ".csv")
 dt <- data.table::data.table(Gnumber = "G1", clid = "CL1", Duration = 72,
                              Concentration = 1, ReadoutValue = 1000)
 data.table::fwrite(dt, path)
 load_long_table(path)

Load manifest

Description

This functions loads and checks the manifest file(s)

Usage

load_manifest(manifest_file)

Arguments

manifest_file

character, file path(s) to manifest(s)

Value

list with manifest data.table and headers

Examples

td <- get_test_data()
 ml <- load_manifest(manifest_path(td))

Load results

Description

This functions loads and checks the results file(s)

Usage

load_results(
  df_results_files,
  instrument = "EnVision",
  headers = gDRutils::get_env_identifiers()
)

Arguments

df_results_files

data.table, with datapaths and names of results file(s) or character with file path of results file(s)
instrument

character
headers

list of headers identified in the manifest file

Value

data.table with results' data

Examples

td <- get_test_data()
 r_df <- load_results(result_path(td))

Load EnVision results from xlsx

Description

This functions loads and checks the results file(s)

Usage

load_results_EnVision(results_file, headers = gDRutils::get_env_identifiers())

Arguments

results_file

character vector containing file path(s) to results file(s)
headers

list of headers identified in the manifest

Value

data.table with results data

Load incucyte results from plain text

Description

This functions loads incucyte time-course cell count file

Usage

load_results_Incucyte(results_file, headers = gDRutils::get_env_identifiers())

Arguments

results_file

list of strings: file paths to result paths from individual plates
headers

list of headers identified in the manifest

Value

data.table derived from Incucyte data

Load tecan results from xlsx

Description

This functions loads and checks the results file

Usage

load_results_Tecan(results_file, headers = gDRutils::get_env_identifiers())

Arguments

results_file

string, file path to a result file
headers

list of headers identified in the manifest

Value

data.table derived from Tecan data

Load results from tsv

Description

This functions loads and checks the results file(s)

Usage

load_results_tsv(results_file, headers)

Arguments

results_file

character, file path(s) to template(s)
headers

list of headers identified in the manifest

Value

data.table with results data

Load templates

Description

This functions loads and checks the template file(s)

Usage

load_templates(df_template_files)

Arguments

df_template_files

data.table, with datapaths and names of results file(s) or character with file path of templates file(s)

Value

data.table with templates data

Examples

td <- get_test_data()
 t_df <- load_templates(template_path(td))

Load templates from tsv

Description

This functions loads and checks the template file(s)

Usage

load_templates_tsv(template_file, template_filename = NULL)

Arguments

template_file

character, file path(s) to template(s)
template_filename

character, file name(s)

Value

data.table with template data

Load templates from xlsx

Description

This functions loads and checks the template file(s)

Usage

load_templates_xlsx(template_file, template_filename = NULL)

Arguments

template_file

character, file path(s) to template(s)
template_filename

character, file name(s)

Value

data.table with templates data

Parse D300

Description

This function parses a D300 *.tdd file (XML format) into a data.table

Usage

parse_D300_xml(D300_file)

Arguments

D300_file

string, file path to D300 .tdd file

Value

data.table representing input D300_file.

Examples

td3 <- get_test_D300_data()
fs <- td3[["f_96w"]]
dose_df <- parse_D300_xml(fs[["d300"]])

Read excel file and transorm it into data.table object

Description

Read excel file and transorm it into data.table object

Usage

read_excel_to_dt(path, ...)

Arguments

path

path to excel file
...

other arguments that should be passed into readxl::read_excel

Value

data.table object with read excel file

Examples

datasets <- readxl::readxl_example("datasets.xlsx")
read_excel_to_dt(datasets)

for each drug create a Gnumber and Concentration information for each well

Description

for each drug create a Gnumber and Concentration information for each well

Usage

save_drug_info_per_well(trt_info, trt_gnumber_conc, wb, idfs)

Arguments

trt_info

list with treatment info
trt_gnumber_conc

list with treatment data
wb

pointer to xlsx workbook
idfs

charvec with identifiers

Value

NULL invisibly.

Adjust environment variables to meet gDR standards

Description

Adjust environment variables to meet gDR standards

Usage

setEnvForPSet()

Value

NULL

Examples

setEnvForPSet()
gDRutils::reset_env_identifiers()

standardize_record_values

Description

map values to a dictionary

Usage

standardize_record_values(x, dictionary = DICTIONARY)

Arguments

x

a named array
dictionary

a named array

Value

a named array with updated names

Examples

standardize_record_values(c("Vehicle", "vehcle"))