predict.ampgram_model: Predict antimicrobial peptides

In AmpGram: Prediction of Antimicrobial Peptides

Description

Recognizes antimicrobial peptides using the AmpGram algorithm.

Usage

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

Arguments

object	ampgram_model object.
newdata	list of sequences (for example as given by read_fasta or read_txt).
...	further arguments passed to or from other methods.

Details

AmpGram requires the external package, AmpGramModel, which contains models necessary to perform the prediction. The model can be installed using install_AmpGramModel.

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

seq

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

all_mers_pred

Numeric vector of predictions for each 10-mer (subsequence of 10 amino acids) of a sequence. Prediction value indicates probability that a 10-mer possesses antimicrobial activity and ranges from 0 (non-AMP) to 1 (AMP).

single_prot_pred

Named numeric vector of a single prediction value for a whole peptide/protein. Its value corresponds to the probability that a peptide/protein exhibits antimicrobial activity. It assumes name TRUE if probability is equal or greater than 0.5, i.e. peptide/protein is classified as antimicrobial (AMP), and FALSE if probability is less that 0.5, i.e. peptide/protein is classified as non-antimicrobial (non-AMP).

Value

list of objects of class single_ampgram_pred. Each object of this class contains analyzed sequence, values of predictions for 10-mers and result of the prediction for the whole peptide/protein.

AmpGram documentation built on July 1, 2020, 7:50 p.m.