corplot: Pairwise Correlation Calculation and Visualization

In GCAI.bias: Guided Correction Approach for Inherited bias (GCAI.bias)

Description

Pairwise comparison matrix of the original and corrected measurements

Usage

corplot(mat)

Arguments

mat	a data matrix from correct.guided function

Details

Pairwise plots of sequencing reads mapped to each base pair on the log10 scale will be shown in the bottom panel; Pairwise Pearson correlation coefficients calculated on data points larger than 1 will be shown in the top panel.

Value

a plot produced on the current graphic device

Author(s)

Guoshuai Cai

References

Cai G, RNA-SEQUENCING APPLICATIONS: GENE EXPRESSION QUANTIFICATION AND METHYLATOR PHENOTYPE IDENTIFICATION, Ph.D. Thesis, 2013

See Also

correct.guided

Examples

word<-81

data(obj.index)
data(train.dat.seq)
data(train.dat.counts)
data(test.dat.seq)
data(test.dat.counts)

#train

train.index<-index.preprocess(train.dat.seq,word)
obj.train<-counts.preprocess(train.dat.counts)
obj.train[["index"]]<-train.index

coe.lm<-lm.estimate(obj.train,fit.cut.train=5)

#test

test.index<-index.preprocess(test.dat.seq,word)
obj.test<-counts.preprocess(test.dat.counts)
obj.test[["index"]]<-test.index

test.corrected<-correct.guided(coe.lm,obj.test)

corplot(test.corrected)

Example output

GCAI.bias documentation built on May 1, 2019, 8:18 p.m.