View source: R/markerScatter.R
markerScatter | R Documentation |
Generates an expression profile of each gene catetory in one sample against another, alternatively plot the regression line from linear modeling fitting.
markerScatter(expr, log = FALSE, samples, cate.gene, markers = NULL, pch = 19, cex = 0.5, col = NULL, xlab = NULL, ylab = NULL, main = NULL, add.line = TRUE, text.cex = 1, legend.labels = NULL, ... )
expr |
a data frame with gene expression. |
log |
logical to determine if the gene expression data is log converted (add a small constant 2), default to FALSE. |
samples |
a vector of samples to compare on the x axis and y axis. |
cate.gene |
a list of the gene categories, alternatively output by |
markers |
vector of marker genes to be highlighted in the plot. No gene is highlighted when it's |
pch, cex, col, xlab, ylab, main |
plot parameters, see details in |
add.line |
logical to determine if the linear model fitting line is added on the figure. |
text.cex |
font size for the text on |
legend.labels |
vector of labels for the marker legend. |
... |
other parameters in |
Visualization of gene expression in the five categories under each pair-wised comparison.
plot with gene expression profile.
#load the marker genes of somatic and primary cells data(markers) data(expr.filter) #scatterplot col = c("#abd9e9", "#2c7bb6", "#fee090", "#d7191c", "#fdae61") markerScatter(expr = expr.filter, log = TRUE, samples = c("CB", "DMEC"), cate.gene = cate.gene[2:4], markers = markers, col = col[2:4], xlab = expression('log'[2]*' expression in CB (target)'), ylab = expression('log'[2]*' expression in DMEC (input)'),main = "")
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