m6Aboost: m6Aboost for identify the m6A peaks from the miCILP2 data

In ZarnackGroup/m6Aboost: m6Aboost

m6Aboost for identify the m6A peaks from the miCILP2 data

Description

An function for calculating the relative signal strength and extracting all the features that required by the m6Aboost model for each peak.

Usage

m6Aboost(object, genome = "", normalization = TRUE)

Arguments

object	A GRanges object which should contains all the single nucleotide peaks of miCLIP2 experiment.
genome	The name of the BSgenome that you are working with. For example "BSgenome.Mmusculus.UCSC.mm10".
normalization	A logical vector which indicates whether you would like normalize the RSS and C to T reads number to the mean value of the training set of the model. This will help to reduce the false positive rate.

Value

A GRanges object with all the information that is required by the m6Aboost model.

Author(s)

You Zhou

Examples

    testpath <- system.file("extdata", package = "m6Aboost")
    test_gff3 <- file.path(testpath, "test_annotation.gff3")
    test <- readRDS(file.path(testpath, "test.rds"))
    test<- preparingData(test, test_gff3, colname_reads="WTmean",
        colname_C2T="CtoTmean")

    ## The input of m6Aboost should be the output from preparingData function
    ## Please make sure that the correct BSgenome package have installed
    ## before running motifProfile. For example,
    ## library("BSgenome.Mmusculus.UCSC.mm10")

    test <- m6Aboost(test, "BSgenome.Mmusculus.UCSC.mm10")

ZarnackGroup/m6Aboost documentation built on Dec. 8, 2023, 11:26 p.m.