| Type: | Package |
| Title: | A Collection of Utility Function from the Inserm/Inria SISTM Team |
| Version: | 0.1.1 |
| Author: | Boris Hejblum [aut], Mélanie Huchon [aut, cre] |
| Maintainer: | Mélanie Huchon <melanie.huchon@u-bordeaux.fr> |
| Description: | Functions common to members of the SISTM team. |
| License: | MIT + file LICENSE |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.1.2 |
| Imports: | BlandAltmanLeh, dplyr, ggbeeswarm, ggplot2, ggrepel, rlang, scales, stats |
| NeedsCompilation: | no |
| Packaged: | 2022-03-23 16:14:49 UTC; mh8 |
| Repository: | CRAN |
| Date/Publication: | 2022-03-24 08:30:02 UTC |
Bland-Altman plot function
Description
Bland-Altman plot function
Usage
BlandAltmanPlot(
var1,
var2,
with_gradient = FALSE,
line_color = c("blue", "lightblue"),
extremum_pctg = TRUE
)
Arguments
var1 |
a vector of numerics for the 1rst group to be compared. |
var2 |
a vector of numerics for the 2nd group to be compared. |
with_gradient |
a logical indicating if you have a lot of measures, use |
line_color |
a vector of color for the three lines : average difference and upper and lower limits of the confidence interval for the average difference. |
extremum_pctg |
a logical indicating if you want to add the percentage of points outside the confidence interval for the upper and lower limits. Default is TRUE. |
Value
a ggplot2 object
Examples
library(ggplot2)
#Small sample
#Generate data
x <- rnorm(30)
y <- rnorm(30, mean = 5, sd = 3)
#Plotting
BlandAltmanPlot(var1 = x, var2 = y)
#Add color by group
gr <- c(rep("G1", 15), rep("G2", 15))
BlandAltmanPlot(var1 = x, var2 = y) + geom_point(aes(color = gr))
#High sample
#Generate data
x <- rnorm(10000)
y <- rnorm(10000, mean = 5, sd = 3)
#Plotting with gradient
BlandAltmanPlot(var1 = x, var2 = y, with_gradient = TRUE)
Multiple boxplots for many times
Description
Multiple boxplots for many times
Usage
multipleBoxplots(data, x_var, y_var, add_points = TRUE)
Arguments
data |
a dataset from which the variable |
x_var |
corresponding to the x coordinates for the plot, it must be a factor to obtain multiple boxplots. |
y_var |
corresponding to the y coordinates for the plot. |
add_points |
if you want to add points on boxplots. Default value is |
Value
a ggplot2 object
Examples
library(ggplot2)
#Generate data
x_ex <- factor(c(rep("J0", 10), rep("J7", 10), rep("J14", 10)), levels = c("J0", "J7", "J14"))
y_ex <- rnorm(30)
data_ex <- cbind.data.frame(x_ex, y_ex)
#Plotting
multipleBoxplots(data = data_ex, x_var = x_ex, y_var = y_ex)
multipleBoxplots(data = data_ex, x_var = x_ex, y_var = y_ex) +
labs(x = "Time", y = "Value") +
theme(legend.position = "none")
Functions
Description
Functions
Usage
normal_distribution(vec)
Arguments
vec |
a |
Value
a vector
sistmr.
Description
This package contains functions common to members of the SISTM team.
Volcano plot function
Description
Volcano plot function
Usage
volcanoPlot(
log2fc,
pValue,
data,
FDR_threshold = 0.05,
LFC_threshold = log2(1.5),
color = c("red", "black"),
geneNames = NULL,
nb_geneTags = 20,
logTransformPVal = TRUE
)
Arguments
log2fc |
a magnitude of change (fold-change) in base log 2 corresponding to the x-axis. |
pValue |
a statistical significance (p-value) corresponding to the y-axis. |
data |
a data.frame of differentially expressed results from which the
variable |
FDR_threshold |
a threshold of false discovery rate. |
LFC_threshold |
a threshold of log fold change. |
color |
a vector of two colors for significant or not significant points. |
geneNames |
a vector of gene names if you want to put gene tags on the volcano plot. Default is NULL. |
nb_geneTags |
number of tags for the significant genes if |
logTransformPVal |
If TRUE, the p-values will have a negative logarithm transformation (base 10). Default is TRUE. |
Value
a ggplot2 object
Examples
genes <- paste0("G", 1:500)
pval <- runif(500, max = 0.5)
log2FC <- runif(500, min = -4, max = 4)
data <- cbind.data.frame(genes, pval, log2FC)
rm(genes, pval, log2FC)
volcanoPlot(log2FC, pval, data, geneNames = genes)