Seq_QC_Plot_Intergenic: QC Plots Sequencing metrics (Alignment)
Description
Plot the fraction of reads confidently mapped to intergenic regions
Usage
Seq_QC_Plot_Intergenic(
metrics_dataframe,
plot_by = "sample_id",
colors_use = NULL,
dot_size = 1,
x_lab_rotate = FALSE,
significance = FALSE,
...
)
Arguments
- metrics_dataframe
data.frame contain Cell Ranger QC Metrics (see Read_Metrics_10X
).
- plot_by
Grouping factor for the plot. Default is to plot as single group with single point per sample.
- colors_use
colors to use for plot if plotting by group. Defaults to RColorBrewer Dark2 palette if
less than 8 groups and DiscretePalette_scCustomize(palette = "polychrome")
if more than 8.
- dot_size
size of the dots plotted if plot_by
is not sample_id
Default is 1.
- x_lab_rotate
logical. Whether to rotate the axes labels on the x-axis. Default is FALSE.
- significance
logical. Whether to calculate and plot p-value comparisons when plotting by
grouping factor. Default is FALSE.
- ...
Other variables to pass to ggpubr::stat_compare_means
when doing significance testing.
Examples
Run this codeif (FALSE) {
Seq_QC_Plot_Intergeneic(metrics_dataframe = metrics)
}
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