predict.cancergram_model {CancerGram}R Documentation

Predict anticancer peptides


Recognizes anticancer peptides using the CancerGram algorithm.


## S3 method for class 'cancergram_model'
predict(object, newdata, ...)



cancergram_model object.


list of sequences (for example as given by read_fasta or read_txt).


further arguments passed to or from other methods.


CancerGram requires the external package, CancerGramModel, which contains models necessary to perform the prediction. The model can be installed using install_CancerGramModel.

Predictions for each protein are stored in objects of class single_cancergram_pred. It consists of three elements:


Character vector of amino acid sequence of an analyzed peptide/protein


Matrix of predictions for each 5-mer (subsequence of 5 amino acids) of a sequence. Each row corresponds to one mer and columns to predicted classes (ACP, AMP or negative). Prediction value indicates probability that a 5-mer possesses anticancer activity (acp), antimicrobial activity (amp) or none of them (neg).


One row matrix of a single prediction value for a whole peptide/protein. Its value corresponds to the probability that a peptide/protein exhibits anticancer activity, antimicrobial activity or none of them.


list of objects of class single_cancergram_pred. Each object of this class contains analyzed sequence, values of predictions for 5-mers and result of the prediction for the whole peptide/protein.

[Package CancerGram version 1.0.0 Index]