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Coloc 1.11

Coloc version 1.11 on CRAN. This version adds two options to deal with variable selection in performing colocalisation testing.  You can now either

  • summarize the genetic variation in a region using principle components, and perform a (likely high df) test over a substantial proportion of these, see functions pcs.prepare() and pcs.model()
  • use Bayesian Model Averaging to average over all possible SNP selections of a fixed size, with some options to trim the model space according to posterior probability of a SNP being involved in either trait in a univariate analysis, see function bma.test.

This means coloc.test() has become a workhorse function, rather than something that is typically called directly, although that option remains available. The BMA approach means the BMA library is now a dependency.


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