How to make a summary plot like below?

Question

[Jianlan]

I tried to create a similar one using 'ggplot' and combine all of them into one plot, but it takes very long time. Is there an easier way to combine the oncoplot, different clinical information and side legends together?

Also, what is the best way to create the oncoplot clustered by groups and sort based one some value? Like the image below, it was build based on subtypes and sorted by mutations rate I guess. The link is below: https://www.researchgate.net/figure/The-mutational-landscape-of-33-cancer-genes-in-Chinese-breast-tumors-n305-Genomic_fig1_332730584

[cmdcolin]

might be GenVisR, not sure if that is a perfect match but it looks fairly similar How to create a mutation landscape (waterfall) plot with GenVisR

Answer 1

[MatthewP]

Try maftools.

Answer 2

[sbstevenlee]

If you are familiar with Python, you may want to check out the fuc package I wrote:

Application Programming Interface (API):

import matplotlib.pyplot as plt
>>> from fuc import common, pymaf
>>> common.load_dataset('tcga-laml')
>>> f = '~/fuc-data/tcga-laml/tcga_laml.maf.gz'
>>> mf = pymaf.MafFrame.from_file(f)
>>> mf.plot_oncoplot()

If you want to create a customized oncoplot like the one shown below, see this tutorial.

Finally, you can also use command line interface (CLI) as well:

$ fuc maf_oncoplt input.maf output.pdf

Answer 3

[Ahmed Alhendi]

I would try the Oncoprint annotation using Complex heatmap here https://jokergoo.github.io/ComplexHeatmap-reference/book/oncoprint.html

Answer 4

[Thind amarinder]

As mentioned by @Ahmed A complex heat map is very useful for customised oncoplot.

I used it for complex visualization, https://www.medrxiv.org/content/10.1101/2022.01.10.22269035v2.full-text