Quickstart

N.B.: This guide won't work for a large whole genomes (like human), but peruse it before heading to working-with-a-whole-genome-variation-graph.

        ## Check out all the cool things vg can do!
        ./bin/vg

        ## see detailed usage instructions for
        ## any command by typing its name w/ no arguments
        ./bin/vg construct
        
        ## Construct - take a reference genome and a VCF and build a graph
        ## VCF must be bgzip'ed and tabix-indexed
        ./bin/vg construct -r reference.fa -v variants.vcf.gz > graph.vg

        ## Maybe you want to see what it looks like?
        ## Better have graphtools installed though.
        ./bin/vg view -d graph.vg | dot -Tpdf -o graph.pdf

        ## Want to map reads? We need two kinds of index first
        ./bin/vg index -x graph.xg -g graph.gcsa -k 11 graph.vg

        ## Ok, now that we have graph.xg and graph.gcsa we can map some reads.
        ## for single end reads:
        ./bin/vg map -x graph.xg -g graph.gcsa -f se_reads.fq > se_reads.gam

        ## For paired-end reads, put your forward reads first and just
        ## use a second -f for your reverse reads
        ./bin/vg map -x graph.xg -g graph.gcsa -f pe_reads_1.fq -f pe_reads_2.fq > pe_reads.gam

        ## Want to call some variants in those reads? Try vg genotype.
        ## First we need to index our new GAM file.
        ## This will make what looks like a directory,
        ## named <my_gam>.index/
        ./bin/vg index -d pe_reads.gam.index -N pe_reads.gam

        ## Now we can genotype our reads. Use -v to get VCF output
        ./bin/vg genotype -v graph.vg pe_reads.gam.index/ > calls.vcf