httk (version 2.7.4)

in.list: Convenience Boolean (yes/no) functions to identify chemical membership in several key lists.

Description

These functions allow easy identification of whether or not a chemical CAS is included in various research projects. While it is our intent to keep these lists up-to-date, the information here is only for convenience and should not be considered to be definitive.

Usage

in.list(
  chem.name = NULL,
  chem.cas = NULL,
  dtxsid = NULL,
  which.list = "ToxCast"
)
is.tox21(chem.cas)
is.toxcast(chem.cas)
is.seem(chem.cas)
is.nhanes(chem.cas)
is.pharma(chem.cas)
is.pfas(chem.cas)

Value

logical

A Boolean (1/0) value that is TRUE if the chemical is in the list.

Arguments

chem.name

One or more Chemical names (spaces and capitalization ignored) -- the chemical must be identified by either CAS, name, or DTXISD

chem.cas

One or more Chemical Abstract Services Registry Numbers (CAS-RN) -- the chemical must be identified by either CAS, name, or DTXISD

dtxsid

One or more of EPA's DSSTox Structure IDs (https://comptox.epa.gov/dashboard) -- the chemical must be identified by either CAS, name, or DTXSIDs

which.list

A character string that can take the following values: "ToxCast", "Tox21", "SEEM", "NHANES", "PFAS", "Pharma" #'

Functions

• is.tox21(): Boolean (yes/no) chemical identity functions

• is.toxcast(): Boolean (yes/no) chemical identity functions

• is.seem(): Boolean (yes/no) chemical identity functions

• is.nhanes(): Boolean (yes/no) chemical identity functions

• is.pharma(): Boolean (yes/no) chemical identity functions

• is.pfas(): Boolean (yes/no) chemical identity functions

Author

John Wambaugh

Details

Tox21: Toxicology in the 21st Century (Tox21) is a U.S. federal High Throughput Screening (HTS) collaboration among EPA, NIH, including National Center for Advancing Translational Sciences and the National Toxicology Program at the National Institute of Environmental Health Sciences, and the Food and Drug Administration. (Bucher et al., 2008)

ToxCast: The Toxicity Forecaster (ToxCast) is a HTS screening project led by the U.S. EPA to perform additional testing of a subset of Tox21 chemicals. (Judson et al. 2010)

SEEM: Systematic Empirical Evaluation of Models is a consensus exposure modeling prediction providing a tentative estimate of daily intake rate in units of mg/kg BW/day for chemicals that may have little information on exposure (Ring et al. 2018)

NHANES: The U.S. Centers for Disease Control (CDC) National Health and Nutrition Examination Survery (NHANES) is an on-going survey to characterize the health and biometrics (e.g., weight, height) of the U.S. population. One set of measurments includes the quantification of xenobiotic chemicals in various samples (blood, serum, urine) of the thousands of surveyed individuals. (CDC, 2014)

References

Bucher, J. R. (2008). Guest Editorial: NTP: New Initiatives, New Alignment. Environ Health Perspect 116(1).

Judson, R. S., Houck, K. A., Kavlock, R. J., Knudsen, T. B., Martin, M. T., Mortensen, H. M., Reif, D. M., Rotroff, D. M., Shah, I., Richard, A. M. and Dix, D. J. (2010). In Vitro Screening of Environmental Chemicals for Targeted Testing Prioritization: The ToxCast Project. Environmental Health Perspectives 118(4), 485-492.

Wambaugh, J. F., Wang, A., Dionisio, K. L., Frame, A., Egeghy, P., Judson, R. and Setzer, R. W. (2014). High Throughput Heuristics for Prioritizing Human Exposure to Environmental Chemicals. Environmental Science & Technology, 10.1021/es503583j.

CDC (2014). National Health and Nutrition Examination Survey. Available at: https://www.cdc.gov/nchs/nhanes.htm.

See Also

is.httk for determining inclusion in httk project

Examples

# \donttest{
httk.table <- get_cheminfo(info=c("CAS","Compound"))
httk.table[,"Rat"] <- ""
httk.table[,"NHANES"] <- ""
httk.table[,"Tox21"] <- ""
httk.table[,"ToxCast"] <- ""
httk.table[,"ExpoCast"] <- ""
httk.table[,"PBTK"] <- ""
# To make this example run quickly, this loop is only over the first five 
# chemicals. To build a table with all available chemicals use:
# for (this.cas in httk.table$CAS)
for (this.cas in httk.table$CAS[1:5])
{
  this.index <- httk.table$CAS==this.cas
  if (is.nhanes(chem.cas=this.cas)) httk.table[this.index,"NHANES"] <- "Y"
  if (is.tox21(chem.cas=this.cas)) httk.table[this.index,"Tox21"] <- "Y"
  if (is.toxcast(chem.cas=this.cas)) httk.table[this.index,"ToxCast"] <- "Y"
  if (is.seem(chem.cas=this.cas)) httk.table[this.index,"ExpoCast"] <- "Y"
  if (is.httk(chem.cas=this.cas,model="PBTK")) httk.table[this.index,"PBTK"] <- "Y"
  if (is.httk(chem.cas=this.cas,species="rat")) httk.table[this.index,"Rat"] <- "Y"
}
# }