httk (version 2.5.0)

load_pradeep2020: Load CLint and Fup QSPR predictions predictions from Pradeep et al. 2020.

Description

This function returns an updated version of chem.physical_and_invitro.data that includes quantitative structure-property relationship (QSPR) predictions from Support Vector Machine and Random Forest models developed and presented in Pradeep et al. 2020, included in pradeep2020.

Usage

load_pradeep2020(overwrite = FALSE, target.env = .GlobalEnv)

Value

data.frame

An updated version of chem.physical_and_invitro.data.

Arguments

overwrite

Only matters if load.image=FALSE. If overwrite=TRUE then existing data in chem.physical_and_invitro.data will be replaced by any predictions in Pradeep et al. (2020) that is for the same chemical and property. If overwrite=FALSE (DEFAULT) then new data for the same chemical and property are ignored. Funbound.plasma values of 0 (below limit of detection) are overwritten either way.

target.env

The environment where the new chem.physical_and_invitro.data is loaded. Defaults to global environment.

Author

Sarah E. Davidson

Details

Because Clint and Fup are the only measurements required for many HTTK models, changing the number of chemicals for which a value is available will change the number of chemicals which are listed with the get_cheminfo command. Use the command reset_httk to return to the initial (measured only) chem.physical_and_invitro.data (for all parameters).

References

pradeep2020chemstrhttk

See Also

reset_httk

get_cheminfo

Examples

# \donttest{
# Count how many chemicals for which HTTK is available without the QSPR:
num.chems <- length(get_cheminfo())
print(num.chems)

# For chemicals with Pradeep et al. (2020) Clint and Fup QSPR predictions, 
# add them to our chemical information wherever measured values are 
# unavailable:
load_pradeep2020()

# Or, for chemicals with Pradeep et al. (2020) QSPR predictions, add them to
# our chemical information but overwrite measured values where we had them:
load_pradeep2020(overwrite=TRUE) 

# Let's see how many chemicals we have now with the Pradeep et al. (2020)
# predictions data loaded:
length(get_cheminfo())

# Now let us reset the chemical data to the initial version:
reset_httk()

# We should be back to our original number:
num.chems == length(get_cheminfo())
# }