M3DropPlottingFunctions {M3Drop} | R Documentation

## Make M3Drop Plots

### Description

Background functions used for making M3Drop plots. Functions tagged with "bg__" are not meant for direct usage and are not available in the Bioconductor release.

### Usage

    	bg__dropout_plot_base(expr_mat, xlim=NA, suppress.plot=FALSE)
    	bg__add_model_to_plot(fitted_model, base_plot, lty=1, lwd=1, col="dodgerblue", legend_loc="topright")
    	bg__highlight_genes(base_plot, expr_mat, genes, col="darkorange", pch=16)

### Arguments

`expr_mat` | a numeric matrix of normalized (not log-transformed) expression values, columns = samples, rows = genes.
`xlim` | limits of x-axis of plot, for comparing distributions across many datasets.
`suppress.plot` | Whether to make the plot or just return values.
`fitted_model` | output from fitting a model to dropout rate vs mean expression, see `bg__fit_MM`,`bg__fit_ZIFA`,`bg__fit_logistic`
`base_plot` | output from `bg__dropout_plot_base`
`legend_loc` | coordinates of top-right corner of the legend.
`genes` | list of genes to be highlighted.
`col,lty,lwd,pch` | Graphical parameters passed to plotted points & lines respectively.

### Details

`bg__dropout_plot_base` plots grey-scale distribution of dropout-rate vs log10(mean expression) for each each. Colour indicates density of points light-grey = low, black = high.

`bg__add_model_to_plot` adds a line based on the predicted dropout rate for each gene from a particular model.

`bg__highlight_genes` highlights specified genes in the given colour.

### Value

`bg__dropout_plot_base` A named list of output: p = dropout rate for each gene s = mean expression of each gene xes = log10 transformed mean expression of each gene data = original expression matrix order = ordering of xes from smallest to largest `bg__add_model_to_plot` Invisibly location of the plotted legend. `bg__highlight_genes` Invisibly the coordinates of the highlighted genes.

[Package M3Drop version 1.14.0 Index]