Coloc v2.3 is up on CRAN.
2013-09-25 Chris Wallace <email@example.com> * v2.3 BUGFIX: Introduced a function to estimate trait variance from supplied coefficients and standard errors. This is used within the approach implemented in coloc.abf(), and replaces the earlier version which implicity assumed that var(Y)=1 for quantitative traits, which could lead to incorrect inference when var(Y) was far from 1.
A new version of wgsea is up on CRAN. It now includes testing with the testthat package, thanks to Olly Burren, and a bugfix for the way propensity weights were generated in the wilcoxon() function.
Coloc v2.2 is up on CRAN. The last two changes are shown below. The important thing is that the arguments to
coloc.abf() have changed. Please do revise your code!
I do try and avoid completely changing arguments to released functions, but in this case, the function was introduced relatively recently, and the change makes sense because it allows us to analyse either datasets for which coefficients and standard errors are available, or for which only p values and minor allele frequencies are available, in a single function.
2013-19-06 Chris Wallace <firstname.lastname@example.org> * v2.2 Merged coloc.abf and coloc.abf.imputed(), so that datasets for wheich beta, var(beta) are available can be matched to datasets with only p values and maf.2 This means the arguments to coloc.abf() have been changed! Please check ?coloc.abf for the new function.
2013-03-06 Chris Wallace <email@example.com> * v2.1 Bug fix for coloc.abf() function, which used p12 instead of log(p12) to calculate L4. New function coloc.abf.imputed() to make better use of fuller information on imputed data.
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 has been included in my coloc package, and I think such a change deserves a bump in version, so coloc v2.0 is now available on CRAN, together with a new vignette, explaining the different methods of analysis available, but see the papers 1 2 for the nitty gritty.
A new version of snpStatsWriter is up on CRAN. It includes a new function,
write.snphap(), for writing snphap files, and a brief vignette has been added, my first vignette written in markdown with knitr.
I’m not absolutely sure I want to learn another markdown syntax, I spend so much time in Org mode that translating from one to another is a pain, but I wanted to give knitr a go and markdown is friendlier than Sweave-like syntax. Perhaps next time I will try ravel to combine org-mode and knitr.
snpStatsWriter is a package to allow “flexible writing of snpStats objects to flat files”. It should help write snpStats objects to disk in formats suitable for reading by snphap, phase, mach, IMPUTE, beagle, and (almost) anything else that expects a rectangular format. All the writing and conversion is done in C, so is fast, even for large datasets.