diff --git a/README.rst b/README.rst index 48cefb3..e5c5304 100644 --- a/README.rst +++ b/README.rst @@ -13,7 +13,7 @@ Quick start guide 2. Convert your VCF(s) to the SMC++ input format with vcf2smc_:: - $ smc++ vcf2smc my.data.vcf.gz out/chr1.smc.gz chr1 Pop1:S1,S2 + $ smc++ vcf2smc my.data.vcf.gz out/example.chr1.smc.gz chr1 Pop1:S1,S2 This command will parse data for the contig ``chr1`` for samples ``S1`` and ``S2`` which are members of population ``Pop1``. You @@ -325,21 +325,21 @@ This command fits two-population clean split models using marginal estimates produced by estimate_. To use ``split``, first estimate each population marginally using ``estimate``:: - $ smc++ vcf2smc my.vcf.gz data/pop1.smc.gz pop1:ind1_1,ind1_2 - $ smc++ vcf2smc my.vcf.gz data/pop2.smc.gz pop2:ind2_1,ind2_2 - $ smc++ estimate -o pop1/ data/pop1.smc.gz - $ smc++ estimate -o pop2/ data/pop2.smc.gz + $ smc++ vcf2smc my.vcf.gz data/pop1..smc.gz pop1:ind1_1,ind1_2 + $ smc++ vcf2smc my.vcf.gz data/pop2..smc.gz pop2:ind2_1,ind2_2 + $ smc++ estimate -o pop1/ data/pop1.chr*.smc.gz + $ smc++ estimate -o pop2/ data/pop2.chr*.smc.gz Next, create datasets containing the joint frequency spectrum for both populations:: - $ smc++ vcf2smc my.vcf.gz data/pop12.smc.gz pop1:ind1_1,ind1_2 pop2:ind2_1,ind2_2 - $ smc++ vcf2smc my.vcf.gz data/pop21.smc.gz pop2:ind2_1,ind2_2 pop1:ind1_1,ind1_2 + $ smc++ vcf2smc my.vcf.gz data/pop12..smc.gz pop1:ind1_1,ind1_2 pop2:ind2_1,ind2_2 + $ smc++ vcf2smc my.vcf.gz data/pop21..smc.gz pop2:ind2_1,ind2_2 pop1:ind1_1,ind1_2 Finally, run ``split`` to refine the marginal estimates into an estimate -of the joint demography:: +of the joint demography using 4 sets of vcf2smc outputs. :: - $ smc++ split -o split/ pop1/model.final.json pop2/model.final.json data/*.smc.gz + $ smc++ split -o split/ pop1/model.final.json pop2/model.final.json data/pop[12]*.chr*.smc.gz $ smc++ plot joint.pdf split/model.final.json posterior