With calculated classification model, identification of the true ORFs among ORF candidates extracted from RNA molecules of interest can be done using function predictORF: model transcript_id start end length prob Where TP – true positive (the positive class is predicted as the positive class number) FN – false negative (the positive class is predicted as the negative class number) FP – false positive (the negative class is predicted as the positive class number) TN – true negative (the negative class is predicted as the negative class number). Load the package with the following command: if (!requireNamespace("BiocManager", quietly = TRUE)) \] The path to the data set trans_sequences.fasta is available as trans <- system.file("extdata", "Set.trans_sequences.fasta", Please, report potential bugs and incompatibilities to usage of the package functions for an automatic determination and annotation of open reading frames (ORFs) is shown for an example set of 50 mRNA molecules loaded from the Ensembl. The ORFhunteR package is considered stable and will undergo few changes from now on. This document describes the usage of the functions integrated in the package and is meant to be a reference document for the end user.
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