This visualization requires several pieces of software to be installed and available.
- R version 3.1.1 or higher
- Python version 2.7.8 or higher
- the Pysam python library
- bedtools
In addition, the following R libraries are used.
- shiny
- ggvis
- ggplot2
Copy "metadata_sample.tsv" to "metadata.tsv", and edit it for your data. The "time.point" column is used to differentiate samples taken contemporaneously vs. from different time points. These should be numbered in chronological order, but the actual numbers used are not important. The special time point 0 indicates a normal sample.
You also need to produce a file of copy number segments, which looks like "segments_sample.tsv", called "segments.tsv". These can be made with the segmentation tool of your choice (eg. DNAcopy, ExomeCNV, TITAN).
Finally, run "collect_vaf.py metadata.tsv /path/to/reference.fa > variants.tsv" to produce a TSV file with variant allelic fractions.
The first time the visualization is run, it will take a long time, and may even time out. This is because it is precomputing statistics about the variants and copy number segments. Subsequent accesses will be much faster.