When analyzing clinical genomes, I often find it hard to visualize the genomic context of a potential driver mutation (say a point mutation on a key cancer gene). For example, is there simultaneous LOH/amplification at the mutation locus? How many copies of the mutant allele are there? Did the mutation arrive before/after the overlapping copy number change? Is there a structural variation breakpoint near by? Are there other point mutations close by?

Thus, I wonder if there is a plotting tool that visualizes a local range of the genome (e.g. a window big enough to inspect a gene) that integrates (in one plot):

1. Point mutations in the region
2. The local copy numbers (major/minor allele if available)
3. SVs affecting the region

Note that the purpose is more to infer the consequence of a mutation as opposed to validating whether the mutation is real or not, which we can already do with a variety tools such as samtools tview.

Circos is a nice format that integrates all three classes of mutations, but it is more for global scale inspections and does not provide enough resolution to zoom into specific gene regions in order to answer the above questions about key mutations of interest. Another close one is IGV, but it does not incorporate allelic specific copy number info.

Thanks!
You can give a try to [karyoploteR](http://bioconductor.org/packages/karyoploteR/). It's an R package to plot data on genomes and can go from single base to the whole genome. Take a look at the [tutorial and examples](https://bernatgel.github.io/karyoploter_tutorial/) to see what it looks like. It's only a plotting tool and does not know much biology, so it can plot almost anything as long as you have it precomputed and can map it to any of the available plot types. Right now it does not have the possibility of plotting individual sequencing reads from a BAM file, if you need that.

A couple of examples of whole genome views. 

Note: Setting `zoom` to a small genomic region in the call to `plotKaryotype` will created a zoomed in version of the plots with the exact same code.

![enter image description here][1]
![enter image description here][2]
![enter image description here][3]


  [1]: https://bernatgel.github.io/karyoploter_tutorial/Examples/SNPArray/images/Figure4-1.png
  [2]: https://bernatgel.github.io/karyoploter_tutorial/Examples/GeneExpression/images/Figure13-1.png
  [3]: https://bernatgel.github.io/karyoploter_tutorial/Examples/Rainfall/images/Figure5-1.png