wheel_plot: Visualize probabilistic classification results

Description Usage Arguments

View source: R/classifier.R

Description

Visualize probabilistic classification results

Usage

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wheel_plot(dge, results_path, mlr_mod = NULL, class_labels = NULL, fig_name,
  colour_by = NULL, facet_by = NULL, style = "points",
  wheel_order = NULL, do.density = NULL)

Arguments

dge

a Seurat object

results_path

folder to place output in

mlr_mod

a glmnet multiclass logistic regression model. Give this or 'class_labels', not both. You can feed the output of 'train_save_classifier' into the 'mlr_mod' argument.

class_labels

atomic character vector naming columns in the Seurat object that contain class probabilities. Give this or 'mlr_mod', not both. If names(class_labels) is filled in, then that's how the spokes get labeled.

fig_name

filename for output.

colour_by

Variable in Seurat object to map color to; default is none

facet_by

Variable in Seurat object to facet resulting plots by; default is none

style

If "points", plot each cell as a dot. If "density", then instead of plotting points, plot 2d density contours. If "hexagons", do AWESOME HEXAGON BINNING YEAHHHHHHH HEXAGONS.

wheel_order

Deprecated.

do.density

Deprecated.

fig_name

filename for output.


maehrlab/thymusatlastools documentation built on May 28, 2019, 2:32 a.m.