visualizeFeature: Visualize Longitudinal Feature

In aametwally/MetaLonDA: Metagenomics Longitudinal Differential Abundance Method

Description

Visualize Longitudinal Feature

Usage

visualizeFeature(
  df,
  text,
  group.levels,
  unit = "days",
  ylabel = "Normalized Count",
  col = c("blue", "firebrick"),
  prefix = "Test"
)

Arguments

df	dataframe has the Count, Group, ID, Time
text	feature name
group.levels	The two level's name
unit	time interval unit
ylabel	text to be shown on the y-axis of all generated figures (default: "Normalized Count")
col	two color to be used for the two groups (eg., c("red", "blue")).
prefix	prefix to be used to create directory for the analysis results

References

Ahmed Metwally ([e-mail])

Examples

data(metalonda_test_data)
pfx = tempfile()
dir.create(file.path(pfx))
n.sample = 5
n.timepoints = 10
n.group = 2
Group = factor(c(rep(0, n.sample*n.timepoints), rep(1, n.sample*n.timepoints)))
Time = rep(rep(1:n.timepoints, times = n.sample), 2)
ID = factor(rep(1:(2*n.sample), each = n.timepoints))
points = seq(1, 10, length.out = 10)
aggregate.df = data.frame(Count = metalonda_test_data[1,], Time = Time, Group = Group, ID = ID)
visualizeFeature(df = aggregate.df, text = rownames(metalonda_test_data)[1], 
group.levels = Group, prefix = pfx)

aametwally/MetaLonDA documentation built on Dec. 26, 2019, 7:46 a.m.