degPlotCluster: Plot clusters from degPattern function output

Description Usage Arguments Value Examples

View source: R/clustering.R

Description

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.

Usage

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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: "
)

Arguments

table

normalized element from degPatterns() output. It can be a data.frame with the following columns in there: genes, sample, expression, cluster, xaxis_column, color_column.

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.

Value

ggplot2 object.

Examples

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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)

DEGreport documentation built on Nov. 8, 2020, 7:23 p.m.