RT.spell: Predict Retention Time

In PaoloBnn/Retip: Retention Time Prediction for Metabolomics

Predict Retention Time

Description

Predict Retention Time

Usage

RT.spell(training, target, model = model, cesc = cesc)

Arguments

training	A training dataset with calculated Chemical Descriptors used in the model
target	A target dataset with calculated Chemical Descriptors where you want to predict Retention Time. The options of the Retip libraty are: "ALL", "HMDB", "KNAPSACK", "CHEBI", "DRUGBANK", "SMPDB", "YMDB", "T3DB", "FOODB", "NANPDB", "STOFF", "BMDB", "LIPIDMAPS", "URINE", "SALIVA", "FECES", "ECMDB", "CSF", "SERUM", "PUBCHEM.1", "PLANTCYC", "UNPD", "BLEXP", "NPA", "COCONUT"
model	A previusly computed model, like Xgboost, Keras etc
cesc	A model for center and scale data calculated with cesc function

Value

Returns target dataframe with Retention time calculated

Examples

# target dataframe needs to have 3 mandatory columns Name, InChIKey and
SMILES and the whole descriptors calculated and not filtered
target_rtp <- RT.spell(training,target,model=xgb)

PaoloBnn/Retip documentation built on June 8, 2024, 6:19 a.m.