R2 Decay Across Distance

[Soul Young]

Hello,

I am trying to fit exponential decay functions of r2 across physical distance of my simulated tree sequences. So far I can retrieve the M x M matrix of r2 of simulations using:

import msprime

tree_sequence=msprime.simulate(sample_size=50, Ne=600, 

                                   length=1e7, recombination_rate=1e-08,

                                  mutation_rate=1e-8)

ld_calc = tskit.LdCalculator(tree_sequence)

A = ld_calc.r2_matrix()

However, I haven't found the best way to turn this matrix into a data structure where I can find the physical distance (in bp) between each SNP in each pairwise computation. 

I can get the M SNP positions with:

variant_positions = [variant.site.position for variant in tree_sequence.variants()]

but after this I'm not sure what's next? I know I can write a VCF of my tree sequences and then compute LD, but I'm trying to keep this computation without producing many intermediate files.

Thanks,

Soul

[Jerome Kelleher]

Hi Soul,

I think this would be a great question for the Q&A section of our tskit
Discussions forum (which we're just starting up). Would you mind posting
it there please?

https://github.com/tskit-dev/tskit/discussions/categories/q-a

Cheers,
Jerome

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[Soul Young]

Ok will do!

Thanks