SEM Graph with t test on cluster level

Perform SEM-based graphs with t-test on cluster level for Seurat objects. Calculates mean expression values and SEM for selected features, and visualizes them. Performs pairwise t-tests comparing conditions, with optional custom control condition and clustering. Optionally returns a summary data frame.

Usage

DO.BarplotClustert(
  Seu_object,
  Feature,
  ListTest = NULL,
  returnValues = FALSE,
  ctrl.condition = NULL,
  group.by = "condition",
  returnPlot = TRUE,
  bar_colours = NULL,
  stat_pos_mod = 1.15,
  step_mod = 0.2,
  x_label_rotation = 45,
  y_limits = NULL,
  log1p_nUMI = T
)

Arguments

Seu_object

Combined Seu_object

ListTest

List for which conditions t-test will be performed, if NULL always against provided CTRL

returnValues

return df.melt.sum data frame containing means and SEM for the set group

ctrl.condition

set your ctrl condition, relevant if running with empty comparison List

group.by

select the seurat object slot where your conditions can be found, default conditon

bar_colours

colour vector

stat_pos_mod

Defines the distance to the graphs of the statistic

step_mod

Defines the distance between each statistics bracket

x_label_rotation

Rotation of x-labels

y_limits

set limits for y-axis

log1p_nUMI

If nUMIs should be log1p transformed

Features

Vector containing featurenames

Value

a ggplot or a dataframe

Author

Mariano Ruz Jurado

Examples

if (FALSE) { # \dontrun{

(optional)
ListTest <- list()
ListTest[[1]] <- c("CTRL", "CONDITION")

DO.BarplotClustert(
  Seu_object = Seurat,
  Features = "CDH5",
  ListTest = ListTest,
  ctrl.condition = "CTRL",
  group.by="condition"
)
} # }