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Run Monocle2 analysis

Source: R/RunMonocle.R
RunMonocle2.Rd

Runs the Monocle2 algorithm on a Seurat object.

Usage

RunMonocle2(
  srt,
  assay = NULL,
  layer = "counts",
  expressionFamily = "negbinomial.size",
  features = NULL,
  feature_type = "HVF",
  disp_filter = "mean_expression >= 0.1 & dispersion_empirical >= 1 * dispersion_fit",
  max_components = 2,
  reduction_method = "DDRTree",
  norm_method = "log",
  residualModelFormulaStr = NULL,
  pseudo_expr = 1,
  root_state = NULL,
  seed = 11
)

Arguments

srt

A Seurat object.

assay

The name of the assay in the Seurat object to use for analysis. Defaults to NULL, in which case the default assay of the object is used.

layer

The layer in the Seurat object to use for analysis. Default is "counts".

expressionFamily

The distribution family to use for modeling gene expression. Default is "negbinomial.size".

features

A vector of gene names or indices specifying the features to use in the analysis. Defaults to NULL, in which case features were determined by feature_type.

feature_type

The type of features to use in the analysis. Possible values are "HVF" for highly variable features or "Disp" for features selected based on dispersion. Default is "HVF".

disp_filter

A string specifying the filter to use when feature_type is "Disp". Default is "mean_expression >= 0.1 & dispersion_empirical >= 1 * dispersion_fit".

max_components

The maximum number of dimensions to use for dimensionality reduction. Default is 2.

reduction_method

The dimensionality reduction method to use. Possible values are "DDRTree" and "UMAP". Default is "DDRTree".

norm_method

The normalization method to use. Possible values are "log" and "none". Default is "log".

residualModelFormulaStr

A model formula specifying the effects to subtract. Default is NULL.

pseudo_expr

Amount to increase expression values before dimensionality reduction. Default is 1.

root_state

The state to use as the root of the trajectory. If NULL, will prompt for user input.

seed

An integer specifying the random seed to use. Default is 11.

Examples

if (interactive()) {
  data("pancreas_sub")
  pancreas_sub <- RunMonocle2(pancreas_sub)
  names(pancreas_sub@tools$Monocle2)
  trajectory <- pancreas_sub@tools$Monocle2$trajectory

  CellDimPlot(
    pancreas_sub,
    group.by = "Monocle2_State",
    reduction = "DDRTree",
    label = TRUE,
    theme_use = "theme_blank"
  ) +
    trajectory
  CellDimPlot(
    pancreas_sub,
    group.by = "Monocle2_State",
    reduction = "UMAP",
    label = TRUE,
    theme_use = "theme_blank"
  )
  FeatureDimPlot(
    pancreas_sub,
    features = "Monocle2_Pseudotime",
    reduction = "UMAP",
    theme_use = "theme_blank"
  )

  pancreas_sub <- RunMonocle2(
    srt = pancreas_sub,
    feature_type = "Disp",
    disp_filter = "mean_expression >= 0.01 & dispersion_empirical >= 1 * dispersion_fit"
  )
  trajectory <- pancreas_sub@tools$Monocle2$trajectory
  CellDimPlot(
    pancreas_sub,
    group.by = "Monocle2_State",
    reduction = "DDRTree",
    label = TRUE,
    theme_use = "theme_blank"
  ) +
    trajectory
  CellDimPlot(
    pancreas_sub,
    group.by = "Monocle2_State",
    reduction = "UMAP",
    label = TRUE,
    theme_use = "theme_blank"
  )
  FeatureDimPlot(
    pancreas_sub,
    features = "Monocle2_Pseudotime",
    reduction = "UMAP",
    theme_use = "theme_blank"
  )
}