Getting started with scatterbars

Below is how to use scatterbar from the provided spatial transcriptomic data from the mouse olfactory bulb tissue sample.

 library(scatterbar)
 data("mOB")
 
 plot(mOB$xy)

 head(mOB$data)

## 1 2 3 4 5
## ACAACTATGGGTTGGCGG 0.1420916 0.05540521 0.2902388 0.00000000 0.1657935
## ACACAGATCCTGTTCTGA 0.0000000 0.77541118 0.0000000 0.00000000 0.0000000
## ACATCACCTGCGCGCTCT 0.3360811 0.00000000 0.0000000 0.32262562 0.3412932
## ACATTTAAGGCGCATGAT 0.2239877 0.00000000 0.0000000 0.55189741 0.2241149
## ACCACTGTAATCTCCCAT 0.1373168 0.08529107 0.2204332 0.00000000 0.0000000
## ACCAGAGCCGTTGAGCAA 0.1364591 0.37986322 0.1499492 0.06702756 0.2147332
## 6 7 8
## ACAACTATGGGTTGGCGG 0.00000000 0.1329341 0.21353679
## ACACAGATCCTGTTCTGA 0.14536750 0.0000000 0.07922131
## ACATCACCTGCGCGCTCT 0.00000000 0.0000000 0.00000000
## ACATTTAAGGCGCATGAT 0.00000000 0.0000000 0.00000000
## ACCACTGTAATCTCCCAT 0.00000000 0.1876818 0.36927715
## ACCAGAGCCGTTGAGCAA 0.05196769 0.0000000 0.00000000

start.time <- Sys.time()
scatterbar::scatterbar(mOB$data, mOB$xy) + ggplot2::coord_fixed()

## Calculated size_x: 1.24034734589208

## Calculated size_y: 0.930260509419063

## Applied padding_x: 0

## Applied padding_y: 0

end.time <- Sys.time()
 print(end.time - start.time)

## Time difference of 0.04842401 secs

We can change the order of how each bar is laid out by changing the order of the cell-type proportion matrix of spatial transcriptomic data. We can also combine scatterbar with other ggplot geoms and customization!

 library(ggplot2)
start.time <- Sys.time()
scatterbar::scatterbar(mOB$data[, c(2,3,4,5,6,7,8,1)], mOB$xy, size_x = 1, size_y = 1, padding_x = 0.1, padding_y = 0.1) +
 geom_point(data=mOB$xy, mapping=aes(x=x, y=y)) +
 theme_bw() + ylab('y') + ggplot2::coord_fixed()

## Calculated size_x: 0.9

## Calculated size_y: 0.9

## Applied padding_x: 0.1

## Applied padding_y: 0.1

end.time <- Sys.time()
 print(end.time - start.time)

## Time difference of 0.09683204 secs