data.NaiveBayes: Training Data

In haibol2016/cleanUpdTSeq: cleanUpdTSeq cleans up artifacts from polyadenylation sites from oligo(dT)-mediated 3' end RNA sequending data

Training Data

Description

A RData containing negative and positive training data

Usage

data.NaiveBayes

Format

A list with 2 data frame, "Negative" and "Positive". Negative has 9219 observations on the following 4120 variables. And Positive is a data frame with 22770 observations on the following 4120 variables. The format is:

list("Negative")

'data.frame': 9219 obs. of 4120 variables:

list("Positive")

'data.frame': 22770 obs. of 4120 variables:

Both of them have same structure.

list("y")

a numeric vector

list("n.A.Downstream")

a numeric vector

list("n.C.Downstream")

a numeric vector

list("n.T.Downstream")

a numeric vector

list("n.G.Downstream")

a numeric vector

list("avg.distanceA2PeakEnd")

a numeric vector

list("dimer")

a numeric vector

: such as AA, AC, AG, AT, CA, ... etc.

a numeric vector

list("heximer")

a factor with levels 0 1

: such as AAAAAA, ACGTAC, ... etc.

a factor with levels 0 1

list("upstream.seq")

a vector of sequence string

list("downstream.seq")

a vector of sequence string

Examples

library(BSgenome.Drerio.UCSC.danRer7)
data(data.NaiveBayes)
head(str(data.NaiveBayes$Negative))
head(str(data.NaiveBayes$Positive))

haibol2016/cleanUpdTSeq documentation built on April 14, 2022, 9:56 p.m.