extractox is a comprehensive R package designed to simplify querying
various chemical, toxicological, and biological databases:
- the Integrated Chemical Environment (ICE) of the National Toxicology Program (NTP).
- the Integrated Risk Information System (IRIS) of the Environmental Protection Agency (EPA).
- the Provisional Peer-Reviewed Toxicity Values (PPRTVs) of EPA.
- the Computational Toxicology Chemicals Dashboard Resource Hub (CompTox) of EPA,
- the monographs of International Agency for Research on Cancer of the World Health Organization (WHO).
- PubChem of the National Center for Biotechnology Information/National Institutes Of Health (NCBI, NIH).
- the Comparative Toxicogenomics Database (CTP) of the MDI Biological Laboratory and NC State University.
The package facilitates interaction with APIs, providing curated and
user-friendly outputs. To communicate with Pubchem, extractox relies
on the packagewebchem.
Install the package extractox from CRAN.
# From CRAN
install.packages("extractox")To get a bug fix or to use a feature from the development version, you
can install the development version of extractox from GitHub.
# Install pak if not already installed
if (!requireNamespace("pak", quietly = TRUE)) {
install.packages("pak")
}
# Install the package from GitHub
pak::pkg_install("c1au6i0/extractox")The ICE database provides access to a variety of data related to chemical toxicity, exposure, and risk assessment. It includes data from high-throughput screening assays, in vivo studies, and computational models.
extr_ice provides access to NTP’s ICE database for toxicological and
exposure-related data.
library(extractox)
# assays is null so all assays are retrieved
ice_data <- extr_ice(casrn = c("50-00-0"), assays = NULL, verbose = FALSE)
names(ice_data)
#> [1] "assay" "endpoint" "substance_type"
#> [4] "casrn" "qsar_ready_id" "value"
#> [7] "unit" "species" "receptor_species"
#> [10] "route" "sex" "strain"
#> [13] "life_stage" "tissue" "lesion"
#> [16] "location" "assay_source" "in_vitro_assay_format"
#> [19] "reference" "reference_url" "dtxsid"
#> [22] "substance_name" "pubmed_id" "query"There are more than 2000 possible assays in ICE. The
extr_ice_assay_names() function allows to search for assay names that
match a pattern you’re interested in. Please note that searches are case
sensitive and accept regexp.
extr_ice_assay_names("Rat Acute", verbose = FALSE) # keep empty to retrieve all
#> [1] "Rat Acute Oral Toxicity" "Rat Acute Inhalation Toxicity"
#> [3] "Rat Acute Dermal Toxicity" "CATMoS, Rat Acute Oral Toxicity"The IRIS database contains information on the health effects of exposure to various substances found in the environment. It provides qualitative and quantitative health risk information.
extr_iris provides access to EPA’s IRIS database and accepts queries
CASRN or IUPAC names of chemicals.
iris_info <- extr_iris(c("glyphosate", "50-00-0"), verbose = FALSE)
names(iris_info)
#> [1] "chemical_name" "casrn"
#> [3] "exposure_route" "assessment_type"
#> [5] "critical_effect_or_tumor_type" "woe_characterization"
#> [7] "toxicity_value_type" "toxicity_value"
#> [9] "query"The extr_pprtv function allows you to extract data for specified
identifiers (CASRN or chemical names) from the EPA’s PPRTVs database.
This function retrieves the file containing all the chemicals and
processes it, but if has an argument (force) to allow users to use a
cached file or force a fresh download.
# Example usage to extract data for a specific CASRN
dat_pprtv_1 <- extr_pprtv(ids = "107-02-8", search_type = "casrn", verbose = FALSE)
# Example usage to extract data for a chemical name
dat_pprtv_2 <- extr_pprtv(ids = "Acrolein", search_type = "name", verbose = FALSE)The CompTox Chemistry Dashboard provides access to data on chemical structures, properties, and associated bioactivity data. It integratesdata from various sources to support chemical safety assessments.
extr_comptox extracts data from CompTox using either CASRN or IUPAC
names of chemicals and returns a list of dataframes.
info_comptox <- extr_comptox(ids = c("Aspirin", "50-00-0"), verbose = FALSE)
names(info_comptox)
#> [1] "comptox_cover_sheet" "comptox_main_data"
#> [3] "comptox_abstract_sifter" "comptox_synonym_identifier"
#> [5] "comptox_related_relationships" "comptox_toxcast_assays_ac50"
#> [7] "comptox_toxval_details" "comptox_chemical_properties"The IARC Monographs database contains evaluations of the carcinogenic risks of various substances to humans. It provides detailed information about Monographs, including publication volumes and years, evaluation years, and additional relevant details.
The function extr_monograph provides access to the WHO IARC Monographs
database and accepts queries using CASRN or the names of chemicals.
dat <- extr_monograph(
search_type = "casrn",
ids = c("105-74-8", "120-58-1"),
verbose = FALSE
)
str(dat)
#> 'data.frame': 2 obs. of 8 variables:
#> $ casrn : chr "105-74-8" "120-58-1"
#> $ agent : chr "Lauroyl peroxide" "Isosafrole"
#> $ group : chr "3" "3"
#> $ volume : chr "36, Sup 7, 71" "10, Sup 7"
#> $ volume_publication_year: chr "1999" "1987"
#> $ evaluation_year : int 1998 1987
#> $ additional_information : chr "" ""
#> $ query : chr "105-74-8" "120-58-1"
# Example usage for name search
dat2 <- extr_monograph(
search_type = "name",
ids = c("Aloe", "Schistosoma", "Styrene")
)
#> ℹ Extracting WHO IARC monographs...
#> Last updated: 2024-11-29 5:08pm (CET)PubChem provides information on chemical structures, identifiers, chemical and physical properties, biological activities, safety and toxicity information, patents, literature citations, and more.
A series of functions that rely on the webchem package are used to
extract chemical information, Globally Harmonized System (GHS)
classification data, or flavor classification (FEMA) from PubChem.
The function extr_chem_info retrieves chemical information of
IUPAC-named chemicals. A warning is displayed if the chemical is not
found.
chem_info <- extr_chem_info(
iupac_names = c("Formaldehyde", "Aflatoxin B1"),
verbose = FALSE
)
names(chem_info)
#> [1] "cid" "iupac_name"
#> [3] "casrn" "cid_all"
#> [5] "casrn_all" "molecular_formula"
#> [7] "molecular_weight" "canonical_smiles"
#> [9] "isomeric_smiles" "inchi"
#> [11] "inchi_key" "iupac_name"
#> [13] "x_log_p" "exact_mass"
#> [15] "monoisotopic_mass" "tpsa"
#> [17] "complexity" "charge"
#> [19] "h_bond_donor_count" "h_bond_acceptor_count"
#> [21] "rotatable_bond_count" "heavy_atom_count"
#> [23] "isotope_atom_count" "atom_stereo_count"
#> [25] "defined_atom_stereo_count" "undefined_atom_stereo_count"
#> [27] "bond_stereo_count" "defined_bond_stereo_count"
#> [29] "undefined_bond_stereo_count" "covalent_unit_count"
#> [31] "volume3d" "x_steric_quadrupole3d"
#> [33] "y_steric_quadrupole3d" "z_steric_quadrupole3d"
#> [35] "feature_count3d" "feature_acceptor_count3d"
#> [37] "feature_donor_count3d" "feature_anion_count3d"
#> [39] "feature_cation_count3d" "feature_ring_count3d"
#> [41] "feature_hydrophobe_count3d" "conformer_model_rmsd3d"
#> [43] "effective_rotor_count3d" "conformer_count3d"
#> [45] "fingerprint2d" "query"Two functions are used to extract specific sections of PubChem chemical information using CASRN:
extr_pubchem_ghsextracts GHS codes.extr_pubchem_femaextracts FEMA data.
ghs_info <- extr_pubchem_ghs(casrn = c("50-00-0", "64-17-5"), verbose = FALSE)
fema_info <- extr_pubchem_fema(casrn = c("50-00-0", "123-68-2"), verbose = FALSE)The function extr_tox is a wrapper used to call all the
above-mentioned functions and retrieve a list of dataframes.
info_tox <- extr_tox(casrn = c("Aspirin", "50-00-0"), verbose = FALSE)The CTP provides information about the interactions between chemicals, genes, and diseases. It helps in understanding the effects of environmental exposures on human health.
A series of functions interact with the CTP database.
extr_ctd extracts information related to chemical-gene or pathway
associations.
input_terms <- c("50-00-0", "64-17-5", "methanal", "ethanol")
ctd_association <- extr_ctd(
input_terms = input_terms,
category = "chem",
report_type = "genes_curated",
input_term_search_type = "directAssociations",
action_types = "ANY",
ontology = c("go_bp", "go_cc"),
verbose = FALSE
)
names(ctd_association)
#> [1] "chemical_name" "chemical_id" "casrn" "gene_symbol"
#> [5] "gene_id" "organism" "organism_id" "pubmed_ids"
#> [9] "query"
# Get expresssion data
ctd_expression <- extr_ctd(
input_terms = input_terms,
report_type = "cgixns",
category = "chem",
action_types = "expression",
verbose = FALSE
)
names(ctd_expression)
#> [1] "chemical_name" "chemical_id" "casrn" "gene_symbol"
#> [5] "gene_id" "organism" "organism_id" "pubmed_ids"
#> [9] "query" NA NATetramers are computationally generated information units that interrelate four data types from the CTP: a chemical, gene product, phenotype, and disease. They help in understanding the complex relationships between these entities and their combined impact on human health.
extr_tetramer extracts info related to tetramers from CTD.
tetramer_data <- extr_tetramer(
chem = c("50-00-0", "ethanol"),
disease = "",
gene = "",
go = "",
input_term_search_type = "directAssociations",
qt_match_type = "equals",
verbose = FALSE
)
names(tetramer_data)
#> [1] "chemical" "chemical_id" "gene" "gene_id" "phenotype"
#> [6] "phenotype_id" "disease" "disease_id" "query"Please note that functions that pull data from EPA servers may encounter
issues on some Linux systems. This is because these servers do not
accept secure legacy renegotiation. On Linux system, those functions
depend on curl and OpenSSL, which have known problems with unsafe
legacy renegotiation in newer versions. One workaround is to downgrade
to curl v7.78.0 and OpenSSL v1.1.1. However, please be aware that
using these older versions might introduce potential security
vulnerabilities. Refer to this
gist
for instructions on how to downgrade curl and OpenSSL on Ubuntu.