bias_histogram {barcodetrackR} | R Documentation |
Given a summarized experiment, gives histogram of log biases for 2 cell types. Each stacked bar in the histogram represents a clone binned by log bias defined as the log2 of the percentage abundance in the sample specified in "bias_1" divided by the percentage abundance in "bias_2."
bias_histogram( your_SE, split_bias_on, bias_1, bias_2, split_bias_over, bias_over = NULL, remove_unique = FALSE, breaks = c(10, 2, 1, 0.5), text_size = 10, linesize = 0.4, ncols = 1, scale_all_y = TRUE, return_table = FALSE )
your_SE |
Your SummarizedExperiment of barcode data and associated metadata |
split_bias_on |
The column in 'colData(your_SE)' from which 'bias_1' and 'bias_2' will be chosen |
bias_1 |
The first cell type (or other factor) to be compared. Must be a possible value of the split_bias_on column of your metadata. Will be on the RIGHT side of the histogram. |
bias_2 |
The second cell type (or other factor) to be compared. Must be a possible value of the split_bias_on column of your metadata. Will be on the LEFT side of the ridge plot |
split_bias_over |
The column in 'colData(your_SE)' that you wish to observe the bias split for. The output will contain a faceted plot: one facet for each value of 'split_bias_over' comparing the samples matching 'bias_1' and 'bias_2' from the 'split_bias_on' argument. |
bias_over |
Choice(s) from the column designated in 'split_bias_over' that will be used for plotting. Defaults to all. |
remove_unique |
If set to true, only clones present in both samples will be considered. |
breaks |
Numeric. The breaks specified for bins on the x-axis (how biased the clones are towards one factor or the other). |
text_size |
The size of the text in the plot. |
linesize |
The linewidth of the stacked bars which represent individual barcodes |
ncols |
Numeric. Number of columns to plot on using plot_grid from cowplot. |
scale_all_y |
Logical. Whether or not to plot all plots on the same y axis limits. |
return_table |
Logical. If set to TRUE, instead of a plot, tbe function will return a list containing a dataframe for each sample-sample log bias combination containing each barcode sequence and its bias between the samples. |
Histogram of log bias for two factors faceted over another set of factors. Or, if return_table is set to TRUE, a list of dataframes containing the log bias data for each bias comparison passed to the function.
data(wu_subset) bias_histogram( your_SE = wu_subset, split_bias_on = "celltype", bias_1 = "B", bias_2 = "T", split_bias_over = "months", ncols = 2 )