R/GEX_trajectories.R
GEX_trajectories.Rd
This is a function which infers trajectories along ordered cells on dimensionality reduced data. It projects trajectrories on a dim. red. plot such as Umap. This uses Monocle3 or Monocle2.
GEX_trajectories(
GEX,
color.cells.by,
reduction.method,
cluster.method,
genes,
label.cell.groups,
label.groups.by.cluster,
labels.per.group,
group.label.size,
monocle.version,
ordering.cells.method
)
GEX output of the VDJ_GEX_matrix function (VDJ_GEX_matrix[[2]]))
Column name in SummarizedExperiment::colData(GEX). To decide how the cells are colored in the output plot. E.g. color.cells.by = 'group_id' the cells will be colored based on their group_id.
Which method to use for dimensionality reduction for monocle3. Supports "UMAP", "tSNE", "PCA" or "LSI". Default value is "UMAP".
Monocle3 gives two clustering options: Using the Leiden or the Louvain algo. Default is louvain.
Takes a vector of genes (e.g. genes = c('CD3E', 'CD4', 'CD8A', 'CD44')) to highlight the expression of these genes in UMAP and in the trajectory plot in monocle3. Default is NULL.
Whether to label cells in each group according to the most frequently occurring label(s) (as specified by color_cells_by) in the group. If false, plot_cells() simply adds a traditional color legend. Default is TRUE
Instead of labeling each cluster of cells, place each label once, at the centroid of all cells carrying that label. Default is TRUE
How many labels to plot for each group of cells. Default is 1
Font size to be used for cell group labels. Default is 1
Version of monocle. Either monocle2 or monocle3. Default is monocle3.
In monocle2 you can choose between selecting genes with high dispersion across cells for ordering cells along a trajectory (= 'high.dispersion'). Or order cells based on genes which differ between clusters, uses an unsupervised procedure called "dpFeature" (= 'differ.genes'). Defalut is "differ.genes"
Returns a list.For monocle3: Element [[1]] returns a cell data set object with a new column for the UMAP clustering. This will be used for the GEX_pseudotime_trajectory_plot() function. [[2]] contains a plot of the clusters. [[3]] contains also a cluster plot but with the inferred trajectories. For monocle2: [[1]] cell data set object. [[2]] Trajetory plot with cells coloured based on their states (important to choose root state for pseudotime plot). [[3]] Trajectory plot based on color.cells.by
if (FALSE) {
trajectory_output <- GEX_trajectories(GEX = vgm[[2]],
reduction.method = "UMAP",
color.cells.by = "group_id",
labels_per_group = 2,
group_label_size = 3)
#visualizing gene expressions
interesting_genes = c("Cxcr6", "Il7r")
genes_trajectories <- GEX_trajectories(GEX = VGM$GEX,
color.cells.by = "group_id",
genes = interesting_genes)
##monocle2 ! DEPRECATED !
#trajectory_output <- GEX_trajectories(GEX = vgm[[2]],
# monocle.version = "monocle2",
# ordering.cells.method = "high.dispersion")
}