Quantify per-gene variation and explore the threshold on the metric of variation to get the desired set of highly variable features.

Creates a page with a scatterplot of the variance of log-expression against the mean log-expression and a table with features and their metrics of variation. With shiny inputs you can color highlight the hvgs in dependency to the proportion and minimal threshold of the relevant variation metric. Also you can download the selcted hvgs or the entire variation metrics table.

add_feature_selection_page(dashboard, object, ...)

# S4 method for i2dashboard,missing
add_feature_selection_page(
  dashboard,
  exprs_values,
  use_function = c("modelGeneVar", "modelGeneVarByPoisson", "modelGeneCV2",
    "modelGeneCV2WithSpikes", "modelGeneVarWithSpikes"),
  title = "Feature selection",
  menu = "Tools",
  ...
)

# S4 method for i2dashboard,SingleCellExperiment
add_feature_selection_page(dashboard, object, exprs_values = "logcounts", ...)

# S4 method for i2dashboard,Seurat
add_feature_selection_page(
  dashboard,
  object,
  assay = "RNA",
  slot = "logcounts",
  ...
)

Arguments

dashboard	A i2dash::i2dashboard.
object	An object of class Seurat::Seurat or SingleCellExperiment::SingleCellExperiment.
...	Further parameters provided to the method specified in use_function.
exprs_values	A numeric matrix of log-counts, or a string indicating the assay of object.
use_function	Choose the scran method to model the variance of the log-expression profiles for each gene.
title	The title of the page.
menu	The name of the menu, under which the page should appear.
assay	In case of a Seurat-class object a string indicating the assay to use.
slot	In case of a Seurat-class object a string indicating the assay to use.

Value

An object of class i2dash::i2dashboard.