Try maftools.

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

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

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

In R, you can build this plot using ggoncoplot. Produces interactive or static versions.

Disclaimer: I built this package

Not shown in picture - but you can sort by any metadata field using the metadata_sort_cols argument.

Other options

• Maftools: great for static plots if your data is in MAF format.
• ComplexHeatmap (oncoPrint): Great tool esp. if you're already comfortable with this package or need very custom plots. Has a very different input requirement to the others. If you have long, tidy data (which is how gene mutation data is often stored in MAFs/databases/etc) - you'll need to do some data wrangling.
• GenVisR has a waterfall plot, similar to ggoncoplot in terms of input format requirements so easy to try both.

If you're comfortable using a web tool for your data - cBioportal oncoprinter is amazing.