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
.
Installation
Install the package extractox
from CRAN.
Features
NTP’s ICE
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.
EPA’s IRIS
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.
EPA’s PPRTVs
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.
EPA’s CompTox
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"
WHO’s IARC
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)
NIH’s PubChem
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_ghs
extracts GHS codes. -
extr_pubchem_fema
extracts FEMA data.
Tox Info
The function extr_tox
is a wrapper used to call all the above-mentioned functions and retrieve a list of dataframes.
MDI’s CTD
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 NA
Tetramers 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"
#> [3] "gene" "gene_id"
#> [5] "phenotype" "phenotype_id"
#> [7] "disease" "disease_id"
#> [9] "evidence_strength_score" "query"
Important Note for Linux Users
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.