predict_self_model: Predicting CMRs sites by user-specific model

In cma2015/PEA-m5C: An integrated R toolkit for plant m5C analysis.

Description

Predicting the m5C through user-specific squences.

Usage

predict_self_model(models,sequence_dir,end = 5,up = 5)

Arguments

models	A dataframe self models and selected feature based extra_model.
sequence_dir	A path representing the filename of the sequence in FASTA format.
up	A integer number, the length of the upstream sequence required.
end	A integer number, the length of the downstream sequence required.

Examples

load(paste0(system.file(package = "PEAm5c"),"/data/samples.Rds"))
aaa <- PEA_ml(pos_sample = pos_sample,neg_sample = neg_sample)
ddd <- extra_model(res = aaa)
ddd
#
eee <- predict_self_model(models = ddd,sequence_dir = paste0(system.file(package = "PEAm5c"),"/data/cdna.fa"))
table(eee[,4])

cma2015/PEA-m5C documentation built on May 17, 2019, 8:05 a.m.