Package 'extractFAERS' reference manual

Title:	Extract Data from FAERS Database
Description:	Provides functions to extract and process data from the FDA Adverse Event Reporting System (FAERS). It facilitates the conversion of raw FAERS data into structured formats for analysis. See Yang et al. (2022) <doi:10.3389/fphar.2021.772768> for related information.
Authors:	Renjun Yang [ctb], Renjun Yang [aut, cre]
Maintainer:	Renjun Yang <rjyang@rcees.ac.cn>
License:	Apache License (>= 2)
Version:	0.1.1
Built:	2025-03-18 16:24:11 UTC
Source:	CRAN

Extract reports with only one drug used from FAERS data

Description

This function processes the FDA Adverse Event Reporting System (FAERS) data to extract reports where only a single drug was administered.

Usage

extract_FAERS_data(
  workingdir = NULL,
  usetempdir = FALSE,
  corenum = NULL,
  startfile = NULL,
  endfile = NULL,
  onlydoextract = FALSE,
  occpextract = NULL
)
extract_FAERS_data(
  workingdir = NULL,
  usetempdir = FALSE,
  corenum = NULL,
  startfile = NULL,
  endfile = NULL,
  onlydoextract = FALSE,
  occpextract = NULL
)

Arguments

`workingdir`	Character vector. The directory containing the decompressed FAERS ASCII folders.
`usetempdir`	Logical. If TRUE, processed files are stored in a temporary directory; otherwise, they are saved in `workingdir`.
`corenum`	Numeric. The number of CPU cores to use for parallel processing. Using more cores reduces processing time.
`startfile`	Numeric. The index of the first file to process in the DRUG and related folders.
`endfile`	Numeric. The index of the last file to process in the DRUG and related folders.
`onlydoextract`	Logical. If TRUE, only extracts data without performing additional combination or filtering steps.
`occpextract`	Character vector. Specifies the occupation categories for data extraction. Defaults to `c("MD", "HP", "PH", "OT")`.

Details

This package includes example data files in extdata:

faers_ascii_2015q1_example.zip: Example dataset 1.
faers_ascii_2015q2_example.zip: Example dataset 2.
faers_ascii_2015q3_example.zip: Example dataset 3.
faers_ascii_2015q4_example.zip: Example dataset 4.
Use system.file("extdata",package = "extractFAERS") to access the folder contain example zip files.

Value

A character vector containing the file paths of the processed folders

Examples

# Example_1 Perform FAERS data preprocessing in one step and
# generate `F_COREDATA_1PS_PROF_STU.RData` in a temporary folder.
# In practice, it is recommended to set `usetempdir = FALSE` and specify `workingdir`
# to prevent the processed results in the temporary folder from being automatically deleted.
extract_FAERS_data(
  workingdir = system.file("extdata", package = "extractFAERS"),
  usetempdir = TRUE,
  corenum = 2,
  startfile = 1,
  endfile = 4,
  onlydoextract = FALSE,
  occpextract = NULL
)

# Example_2 Stepwise FAERS data preprocessing
# Setting `onlydoextract = TRUE` extracts only single-drug cases and organizes file paths.
# The processed file paths are saved in a temporary directory.
extractfaerspath <- extract_FAERS_data(
  workingdir = system.file("extdata", package = "extractFAERS"),
  usetempdir = TRUE,
  corenum = 2,
  startfile = 1,
  endfile = 4,
  onlydoextract = TRUE,
  occpextract = NULL
)
print(extractfaerspath)

# Filter data based on reporter occupation
# By default, only reports from healthcare professionals
# (e.g., physicians, pharmacists) are retained.
faers1psprofdata <- filter_by_occp_FAERS(
  workingdir = extractfaerspath,
  occpextract = NULL,
  savetoRData = TRUE
)

# Standardize time units to days
# This ensures consistency in the dataset and facilitates analysis of adverse reactions
# based on patient age.
time_to_day_FAERS(
workingdir = extractfaerspath,
usexistRData = TRUE,
filteres = NULL
)

# Example_1 Perform FAERS data preprocessing in one step and
# generate `F_COREDATA_1PS_PROF_STU.RData` in a temporary folder.
# In practice, it is recommended to set `usetempdir = FALSE` and specify `workingdir`
# to prevent the processed results in the temporary folder from being automatically deleted.
extract_FAERS_data(
  workingdir = system.file("extdata", package = "extractFAERS"),
  usetempdir = TRUE,
  corenum = 2,
  startfile = 1,
  endfile = 4,
  onlydoextract = FALSE,
  occpextract = NULL
)

# Example_2 Stepwise FAERS data preprocessing
# Setting `onlydoextract = TRUE` extracts only single-drug cases and organizes file paths.
# The processed file paths are saved in a temporary directory.
extractfaerspath <- extract_FAERS_data(
  workingdir = system.file("extdata", package = "extractFAERS"),
  usetempdir = TRUE,
  corenum = 2,
  startfile = 1,
  endfile = 4,
  onlydoextract = TRUE,
  occpextract = NULL
)
print(extractfaerspath)

# Filter data based on reporter occupation
# By default, only reports from healthcare professionals
# (e.g., physicians, pharmacists) are retained.
faers1psprofdata <- filter_by_occp_FAERS(
  workingdir = extractfaerspath,
  occpextract = NULL,
  savetoRData = TRUE
)

# Standardize time units to days
# This ensures consistency in the dataset and facilitates analysis of adverse reactions
# based on patient age.
time_to_day_FAERS(
workingdir = extractfaerspath,
usexistRData = TRUE,
filteres = NULL
)

Filter extracted FAERS data by reporter occupation

Description

Filter extracted FAERS data by reporter occupation

Usage

filter_by_occp_FAERS(
  workingdir = NULL,
  temp_dir = NULL,
  occpextract = NULL,
  savetoRData = FALSE
)
filter_by_occp_FAERS(
  workingdir = NULL,
  temp_dir = NULL,
  occpextract = NULL,
  savetoRData = FALSE
)

Arguments

`workingdir`	Character vector. The directory containing decompressed FAERS ASCII folders.
`temp_dir`	Internal parameter used only when `extract1PSFAERS` is called internally. Do not modify.
`occpextract`	Character vector. Specifies the occupation types to extract. Defaults to `c("MD", "HP", "PH", "OT")`.
`savetoRData`	Logical. Determines whether to save `F_COREDATA_1PS_PROF.RData` in the working directory. Must be set to `TRUE` if `filter_by_occu_FAERS` is used independently.

Details

This package includes example data files in extdata:

faers_ascii_2015q1_example.zip: Example dataset 1.
faers_ascii_2015q2_example.zip: Example dataset 2.
faers_ascii_2015q3_example.zip: Example dataset 3.
faers_ascii_2015q4_example.zip: Example dataset 4.
Use system.file("extdata",package = "extractFAERS") to access the folder contain example zip files.

Value

A list containing six data frames, containing formatted FAERS data after selecting single-drug cases and filtering reports based on reporter occupation. Can be used by time_to_day_FAERS() to standardize time units.

Examples

# Example_1 Perform FAERS data preprocessing in one step and
# generate `F_COREDATA_1PS_PROF_STU.RData` in a temporary folder.
# In practice, it is recommended to set `usetempdir = FALSE` and specify `workingdir`
# to prevent the processed results in the temporary folder from being automatically deleted.
extract_FAERS_data(
  workingdir = system.file("extdata", package = "extractFAERS"),
  usetempdir = TRUE,
  corenum = 2,
  startfile = 1,
  endfile = 4,
  onlydoextract = FALSE,
  occpextract = NULL
)

# Example_2 Stepwise FAERS data preprocessing
# Setting `onlydoextract = TRUE` extracts only single-drug cases and organizes file paths.
# The processed file paths are saved in a temporary directory.
extractfaerspath <- extract_FAERS_data(
  workingdir = system.file("extdata", package = "extractFAERS"),
  usetempdir = TRUE,
  corenum = 2,
  startfile = 1,
  endfile = 4,
  onlydoextract = TRUE,
  occpextract = NULL
)
print(extractfaerspath)

# Filter data based on reporter occupation
# By default, only reports from healthcare professionals
# (e.g., physicians, pharmacists) are retained.
faers1psprofdata <- filter_by_occp_FAERS(
  workingdir = extractfaerspath,
  occpextract = NULL,
  savetoRData = TRUE
)

# Standardize time units to days
# This ensures consistency in the dataset and facilitates analysis of adverse reactions
# based on patient age.
time_to_day_FAERS(
workingdir = extractfaerspath,
usexistRData = TRUE,
filteres = NULL
)

# Example_1 Perform FAERS data preprocessing in one step and
# generate `F_COREDATA_1PS_PROF_STU.RData` in a temporary folder.
# In practice, it is recommended to set `usetempdir = FALSE` and specify `workingdir`
# to prevent the processed results in the temporary folder from being automatically deleted.
extract_FAERS_data(
  workingdir = system.file("extdata", package = "extractFAERS"),
  usetempdir = TRUE,
  corenum = 2,
  startfile = 1,
  endfile = 4,
  onlydoextract = FALSE,
  occpextract = NULL
)

# Example_2 Stepwise FAERS data preprocessing
# Setting `onlydoextract = TRUE` extracts only single-drug cases and organizes file paths.
# The processed file paths are saved in a temporary directory.
extractfaerspath <- extract_FAERS_data(
  workingdir = system.file("extdata", package = "extractFAERS"),
  usetempdir = TRUE,
  corenum = 2,
  startfile = 1,
  endfile = 4,
  onlydoextract = TRUE,
  occpextract = NULL
)
print(extractfaerspath)

# Filter data based on reporter occupation
# By default, only reports from healthcare professionals
# (e.g., physicians, pharmacists) are retained.
faers1psprofdata <- filter_by_occp_FAERS(
  workingdir = extractfaerspath,
  occpextract = NULL,
  savetoRData = TRUE
)

# Standardize time units to days
# This ensures consistency in the dataset and facilitates analysis of adverse reactions
# based on patient age.
time_to_day_FAERS(
workingdir = extractfaerspath,
usexistRData = TRUE,
filteres = NULL
)

Change all time units to days in the data filtered by filter_by_occu_FAERS(). This function converts age and time units in the data to days, and processes occupation and reaction data.

Description

Change all time units to days in the data filtered by filter_by_occu_FAERS(). This function converts age and time units in the data to days, and processes occupation and reaction data.

Usage

time_to_day_FAERS(workingdir = NULL, usexistRData = FALSE, filteres = NULL)
time_to_day_FAERS(workingdir = NULL, usexistRData = FALSE, filteres = NULL)

Arguments

`workingdir`	Directory containing `F_COREDATA_1PS_PROF.RData`.
`usexistRData`	Logical. Specifies whether to use `F_COREDATA_1PS_PROF.RData` in the working directory for calculations. Must be set to `TRUE` and `workingdir` must be provided if `time_to_day_FAERS` is used independently.
`filteres`	Filtered results for changing time units. Used only when `extract1PSFAERS` is called internally. Set to `NULL` if `time_to_day_FAERS` is used separately.

Details

This package includes example data files in extdata:

faers_ascii_2015q1_example.zip: Example dataset 1.
faers_ascii_2015q2_example.zip: Example dataset 2.
faers_ascii_2015q3_example.zip: Example dataset 3.
faers_ascii_2015q4_example.zip: Example dataset 4.
Use system.file("extdata",package = "extractFAERS") to access the folder contain example zip files.

Value

A character vector containing the path of the processed file "F_COREDATA_1PS_PROF_STU.RData", which can be used for further analysis

Examples

# Example_1 Perform FAERS data preprocessing in one step and
# generate `F_COREDATA_1PS_PROF_STU.RData` in a temporary folder.
# In practice, it is recommended to set `usetempdir = FALSE` and specify `workingdir`
# to prevent the processed results in the temporary folder from being automatically deleted.
extract_FAERS_data(
  workingdir = system.file("extdata", package = "extractFAERS"),
  usetempdir = TRUE,
  corenum = 2,
  startfile = 1,
  endfile = 4,
  onlydoextract = FALSE,
  occpextract = NULL
)

# Example_2 Stepwise FAERS data preprocessing
# Setting `onlydoextract = TRUE` extracts only single-drug cases and organizes file paths.
# The processed file paths are saved in a temporary directory.
extractfaerspath <- extract_FAERS_data(
  workingdir = system.file("extdata", package = "extractFAERS"),
  usetempdir = TRUE,
  corenum = 2,
  startfile = 1,
  endfile = 4,
  onlydoextract = TRUE,
  occpextract = NULL
)
print(extractfaerspath)

# Filter data based on reporter occupation
# By default, only reports from healthcare professionals
# (e.g., physicians, pharmacists) are retained.
faers1psprofdata <- filter_by_occp_FAERS(
  workingdir = extractfaerspath,
  occpextract = NULL,
  savetoRData = TRUE
)

# Standardize time units to days
# This ensures consistency in the dataset and facilitates analysis of adverse reactions
# based on patient age.
time_to_day_FAERS(
workingdir = extractfaerspath,
usexistRData = TRUE,
filteres = NULL
)

# Example_1 Perform FAERS data preprocessing in one step and
# generate `F_COREDATA_1PS_PROF_STU.RData` in a temporary folder.
# In practice, it is recommended to set `usetempdir = FALSE` and specify `workingdir`
# to prevent the processed results in the temporary folder from being automatically deleted.
extract_FAERS_data(
  workingdir = system.file("extdata", package = "extractFAERS"),
  usetempdir = TRUE,
  corenum = 2,
  startfile = 1,
  endfile = 4,
  onlydoextract = FALSE,
  occpextract = NULL
)

# Example_2 Stepwise FAERS data preprocessing
# Setting `onlydoextract = TRUE` extracts only single-drug cases and organizes file paths.
# The processed file paths are saved in a temporary directory.
extractfaerspath <- extract_FAERS_data(
  workingdir = system.file("extdata", package = "extractFAERS"),
  usetempdir = TRUE,
  corenum = 2,
  startfile = 1,
  endfile = 4,
  onlydoextract = TRUE,
  occpextract = NULL
)
print(extractfaerspath)

# Filter data based on reporter occupation
# By default, only reports from healthcare professionals
# (e.g., physicians, pharmacists) are retained.
faers1psprofdata <- filter_by_occp_FAERS(
  workingdir = extractfaerspath,
  occpextract = NULL,
  savetoRData = TRUE
)

# Standardize time units to days
# This ensures consistency in the dataset and facilitates analysis of adverse reactions
# based on patient age.
time_to_day_FAERS(
workingdir = extractfaerspath,
usexistRData = TRUE,
filteres = NULL
)

Package 'extractFAERS'

Help Index

Extract reports with only one drug used from FAERS data

Description

Usage

Arguments

Details

Value

Examples

Filter extracted FAERS data by reporter occupation

Description

Usage

Arguments

Details

Value

Examples

Change all time units to days in the data filtered by filter_by_occu_FAERS(). This function converts age and time units in the data to days, and processes occupation and reaction data.

Description

Usage

Arguments

Details

Value

Examples