edawson / svaha Goto Github PK

Make variation graphs from structural variants:
[x] Deletions [x] Inversions [x] Insertions [x] SNPs [ ] Duplications [ ] Transversions [ ] Breakpoints

Don't worry: we'll be adding these as time permits.

svaha is a small program that converts Variant Call Format (VCF) records into Graphical Fragment Assembly format (i.e. sequence graphs like those in vg). It does so using a minimal single-base graph representation, the world's smallest and least-safe VCF parser (well, probably), and almost no dependencies.

svaha brings in its own libraries, except for zlib. Make sure to have zlib installed. It uses a frozen version of htslib and floating versions of gfakluge. To build svaha:

            git clone --recursive https://github.com/edawson/svaha
            make

and that should do it.

svaha takes a FASTA file and a VCF as arguments:
./svaha -r MYFASTA.fa -v MYVARIATION.vcf

and outputs sorted GFA, which is text-based and easily exchangeable to other, more useful programs (like vg).

-r: a fasta reference
-v: a vcf containing variants (must be relative to the given fasta)
-m: maximum node size. When creating graphs for vg, make sure to use a maximum node size of between 32 and 1023.
1023 is a hard limit (nothing 1024 or over will be indexable) and below 32 the graph begins to eat tons of memory. I tend to use -m 64 or -m 128.

1. Build a variation graph with svaha containing structural variants
2. Reduce node size with a cat result.gfa | vg view -F -v - | vg mod -X 1000 - > new_graph.vg to make the resulting graph indexable with GCSA2.
3. Map reads to that graph using vg map
4. Call variants using vg call or vg genotype

Reach out to me (@edawson) on GitHub and I'll do my best to help!