plotDiffCor {corTest} | R Documentation |
Scatter Plot of 2 Genes for Cases and Controls
Description
Scatter plot of 2 genes for cases and controls, superimposed with linear regression lines.
Usage
plotDiffCor(x1,
z1,
x0,
z0,
pval = NULL,
xlab = "gene1",
ylab = "gene2",
title = "scatter plots")
Arguments
x1 |
numeric. vector of gene expression for gene 1 for cases. |
z1 |
numeric. vector of gene expression for gene 2 for cases. |
x0 |
numeric. vector of gene expression for gene 1 for controls. |
z0 |
numeric. vector of gene expression for gene 2 for controls. |
pval |
numeric. p-value for testing differential correlation of the 2 genes between cases and controls. |
xlab |
character. label for x-axis. |
ylab |
character. label for y-axis. |
title |
character. plot title. |
Value
A list with 4 elments:
g |
A ggplot2 object. |
dat |
a data frame with 3 variables: x, z, and grp. |
coef1 |
a vector of length two giving the intercept and slope of linear regression for cases. |
coef0 |
a vector of length two giving the intercept and slope of linear regression for controls. |
Author(s)
Danyang Yu <dyu33@jhu.edu>, Weiliang Qiu <weiliang.qiu@gmail.com>
References
Danyang Yu, Zeyu Zhang, Kimberly Glass, Jessica Su, Dawn L. DeMeo, Kelan Tantisira, Scott T. Weiss, Weiliang Qiu(corresponding author). New Statistical Methods for Constructing Robust Differential Correlation Networks to characterize the interactions among microRNAs. Scientific Reports 9, Article number: 3499 (2019)
Examples
library(Biobase)
set.seed(1234567)
res = generate_data(n1 = 50, n2 = 60, p1 = 5, p2 = 50)
es = res$es
print(es)
# gene expression data
dat = exprs(es)
print(dim(dat))
print(dat[1:2,1:3])
# 3rd gene
x = dat[3,]
# 5th gene
z = dat[5,]
# for cases
x1 = x[which(es$grp == 1)]
z1 = z[which(es$grp == 1)]
# for controls
x0 = x[which(es$grp == 0)]
z0 = z[which(es$grp == 0)]
# st5
res2 = st5(x1 = x1, z1 = z1, x0 = x0, z0 = z0)
pval = res2$pval
plotDiffCor(x1 = x1,
z1 = z1,
x0 = x0,
z0 = z0,
pval = pval,
xlab = "gene3",
ylab = "gene5",
title = "scatter plots"
)