I am a co-author on another paper about colocalisation posted on arXiv. It’s a novel approach, using Bayesian inference based on Approximate Bayes Factors derived from p values, making colocalisation testing much more practical when data is not often as open access as claimed. My co-author, Vincent Plagnol, has written a nice post about it on Haldane’s Sieve. The software to conduct these tests is in the coloc package, v2.0 now available on CRAN.
We have revised our paper on arXiv detailing some work on colocalisation analysis, a method to determine whether two traits share a common causal variant.
I have been following the debate about open peer review: not just reviewers for traditional journals signing their reviews, but the idea of community-sourced peer review: you publish your paper when you are happy with it, other scientists comment and point out weaknesses, you revise it appropriately and publicly. This all sounds like a great idea, and is part of why this paper was first published on arXiv. I really care about the appropriate use of statistical methods for colocalisation and think the topic of data integration is an important one. Having the paper on arXiv has been useful for sharing my paper with others, and for giving a reference url in talks. But, although some people have told me they read it, and I know some are using the software, no one has given me any criticism of the paper itself.