View source: R/get_functions.R
get_pairwise_sharing | R Documentation |
Compute the proportion of (significant) signals shared by magnitude in each pair of conditions, based on the poterior mean
get_pairwise_sharing(m, factor = 0.5, lfsr_thresh = 0.05, FUN = identity)
m |
the mash fit |
factor |
a number in [0,1] the factor within which effects are considered to be shared |
lfsr_thresh |
the lfsr threshold for including an effect in the assessment |
FUN |
a function to be applied to the estimated effect sizes before assessing sharing. The most obvious choice beside the default 'FUN=identity' would be 'FUN=abs' if you want to ignore the sign of the effects when assesing sharing. |
For each pair of tissues, first identify the effects that are significant (by lfsr<lfsr_thresh) in at least one of the two tissues. Then compute what fraction of these have an estimated (posterior mean) effect size within a factor 'factor' of one another. The results are returned as an R by R matrix.
simdata = simple_sims(50,5,1)
data = mash_set_data(simdata$Bhat, simdata$Shat)
m = mash(data, cov_canonical(data))
get_pairwise_sharing(m) # sharing by magnitude (same sign)
get_pairwise_sharing(m, factor=0) # sharing by sign
get_pairwise_sharing(m, FUN=abs) # sharing by magnitude when sign is ignored
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