packages <- c( "CIMseq", "printr", "ggthemes", "dplyr", "tidyr", "ggplot2", "viridis" ) purrr::walk(packages, library, character.only = TRUE) rm(packages)
Plot markers.
plotCountsMarkers( CIMseqSinglets_test, CIMseqMultiplets_test, markers = c("CD74", "ANXA3") )
Plot cell number.
plotCountsERCC(CIMseqSinglets_test, CIMseqMultiplets_test)
Get the plotting data so you can make a custom plot.
plotCountsMarkers( CIMseqSinglets_test, CIMseqMultiplets_test, markers = c("CD74", "ANXA3") ) %>% plotData() %>% head() plotCountsERCC(CIMseqSinglets_test, CIMseqMultiplets_test) %>% plotData() %>% head()
Plot the clustering and classification.
plotUnsupervisedClass(CIMseqSinglets_test, CIMseqMultiplets_test)
Plot a single marker.
plotUnsupervisedMarkers(CIMseqSinglets_test, CIMseqMultiplets_test, "CD74")
Plot markers in different cell types.
plotUnsupervisedMarkers( CIMseqSinglets_test, CIMseqMultiplets_test, markers = c("CD74", "ANXA3", "ACTG2") )
Plot mean of multiple markers for the same cell type.
#use the data instead plotUnsupervisedMarkers( CIMseqSinglets_test, CIMseqMultiplets_test, markers = c("CD74", "HLA-DRA", "IL13RA2", "MAGEA4") ) %>% plotData() %>% gather(gene, value, -Sample, -(`Sample type`:Colour)) %>% group_by(Sample) %>% mutate(`Mean(markers)` = mean(value)) %>% ungroup() %>% select(`dim.red dim 1`, `dim.red dim 2`, `Mean(markers)`) %>% distinct() %>% ggplot() + geom_point(aes(`dim.red dim 1`, `dim.red dim 2`, colour = `Mean(markers)`)) + viridis::scale_colour_viridis(option = "E") + theme_few() + theme(legend.position = "top", legend.title.align = 0) + guides(colour = guide_colourbar(title.position = "top"))
Get the plotting data so you can make a custom plot.
plotUnsupervisedClass(CIMseqSinglets_test, CIMseqMultiplets_test) %>% plotData() %>% head() plotUnsupervisedMarkers( CIMseqSinglets_test, CIMseqMultiplets_test, markers = c("CD74", "ANXA3", "ACTG2") ) %>% plotData %>% head()
plotSwarmGraph(CIMseqSwarm_test, CIMseqSinglets_test, CIMseqMultiplets_test)
plotSwarmCircos( CIMseqSwarm_test, CIMseqSinglets_test, CIMseqMultiplets_test, alpha = 1 )
Get data to make a custom plot.
plotSwarmGraph(CIMseqSwarm_test, CIMseqSinglets_test, CIMseqMultiplets_test) %>% plotData()
#taking too long... why? plotSwarmGenes( CIMseqSwarm_test, CIMseqSinglets_test, CIMseqMultiplets_test, c("CD74", "ANXA3", "ACTG2"), rownames(getData(CIMseqSwarm_test, "fractions")) )
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