View source: R/plotFunctions.R
plotMarkerMap | R Documentation |
Given some reduced dimensional representation of the data (such as UMAP or tSNE) that has been calculated however you would like, this provides a way to visualise how likely a set of genes are to be soup derived on that map. That is, given a set of genes, this function calculates how many counts would be expected if that droplet were nothing but soup and compares that to the observed count. This is done via a log2 ratio of the two values. A Poisson test is performed and points that have a statistically significant enrichment over the background (at 5
plotMarkerMap( sc, geneSet, DR, ratLims = c(-2, 2), FDR = 0.05, useToEst = NULL, pointSize = 2, pointShape = 21, pointStroke = 0.5, naPointSize = 0.25 )
sc |
SoupChannel object. |
geneSet |
A vector with the names of the genes to aggregate and plot evidence for. |
DR |
A data.frame, with rows named by unique cell IDs (i.e., <ChannelName>_<Barcode>) the first two columns of which give the coordinates of each cell in some reduced dimension representation of the data. Try and fetch automatically if missing. |
ratLims |
Truncate log ratios at these values. |
FDR |
False Discovery Rate for statistical test of enrichment over background. |
useToEst |
A vector (usually obtained from |
pointSize |
Size of points |
pointShape |
Shape of points |
pointStroke |
Stroke size for points |
naPointSize |
Point size for NAs. |
A ggplot2 containing the plot.
gg = plotMarkerMap(scToy,'CD7')
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