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18 changes: 9 additions & 9 deletions README.rst
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Expand Up @@ -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
Expand Down Expand Up @@ -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 <contig> pop1:ind1_1,ind1_2
$ smc++ vcf2smc my.vcf.gz data/pop2.smc.gz <contig> pop2:ind2_1,ind2_2
$ smc++ estimate -o pop1/ <mu> data/pop1.smc.gz
$ smc++ estimate -o pop2/ <mu> data/pop2.smc.gz
$ smc++ vcf2smc my.vcf.gz data/pop1.<contig>.smc.gz <contig> pop1:ind1_1,ind1_2
$ smc++ vcf2smc my.vcf.gz data/pop2.<contig>.smc.gz <contig> pop2:ind2_1,ind2_2
$ smc++ estimate -o pop1/ <mu> data/pop1.chr*.smc.gz
$ smc++ estimate -o pop2/ <mu> 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 <contig> pop1:ind1_1,ind1_2 pop2:ind2_1,ind2_2
$ smc++ vcf2smc my.vcf.gz data/pop21.smc.gz <contig> pop2:ind2_1,ind2_2 pop1:ind1_1,ind1_2
$ smc++ vcf2smc my.vcf.gz data/pop12.<contig>.smc.gz <contig> pop1:ind1_1,ind1_2 pop2:ind2_1,ind2_2
$ smc++ vcf2smc my.vcf.gz data/pop21.<contig>.smc.gz <contig> 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
Expand Down