M3D_Plotting: Make M3Drop Plots
In M3Drop: Michaelis-Menten Modelling of Dropouts in single-cell RNASeq

Description Usage Arguments Details Value

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.

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	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)

`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.

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.

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.

M3Drop documentation built on Nov. 8, 2020, 5:06 p.m.