degPlotCluster | R Documentation |
This function helps to format the cluster plots from degPatterns()
.
It allows to control the layers and it returns a ggplot object that
can accept more ggplot functions to allow customization.
degPlotCluster(
table,
time,
color = NULL,
min_genes = 10,
process = FALSE,
points = TRUE,
boxes = TRUE,
smooth = TRUE,
lines = TRUE,
facet = TRUE,
cluster_column = "cluster",
prefix_title = "Group: "
)
table |
|
time |
column name to use in the x-axis. |
color |
column name to use to color and divide the samples. |
min_genes |
minimum number of genes to be added to the plot. |
process |
whether to process the table if it is not ready for plotting. |
points |
Add points to the plot. |
boxes |
Add boxplot to the plot. |
smooth |
Add regression line to the plot. |
lines |
Add gene lines to the plot. |
facet |
Split figures based on cluster ID. |
cluster_column |
column name if cluster is in a column with a different name. Usefull, to plot cluster with different cutoffs used when grouping genes from the clustering step. |
prefix_title |
text to add before the cluster ID in the figure title. |
ggplot2 object.
data(humanGender)
library(SummarizedExperiment)
library(ggplot2)
ma <- assays(humanGender)[[1]][1:100,]
des <- colData(humanGender)
des[["other"]] <- sample(c("a", "b"), 85, replace = TRUE)
res <- degPatterns(ma, des, time="group", col = "other", plot = FALSE)
degPlotCluster(res$normalized, "group", "other")
degPlotCluster(res$normalized, "group", "other", lines = FALSE)
library(dplyr)
library(tidyr)
library(tibble)
table <- rownames_to_column(as.data.frame(ma), "genes") %>%
gather("sample", "expression", -genes) %>%
right_join(distinct(res$df[,c("genes", "cluster")]),
by = "genes") %>%
left_join(rownames_to_column(as.data.frame(des), "sample"),
by = "sample") %>%
as.data.frame()
degPlotCluster(table, "group", "other", process = TRUE)
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