get_pairwise_sharing_from_samples: Compute the proportion of (significant) signals shared by...

In mashr: Multivariate Adaptive Shrinkage

Compute the proportion of (significant) signals shared by magnitude in each pair of conditions

Description

Compute the proportion of (significant) signals shared by magnitude in each pair of conditions

Usage

get_pairwise_sharing_from_samples(
  m,
  factor = 0.5,
  lfsr_thresh = 0.05,
  FUN = identity
)

Arguments

m	the mash fit with samples from posteriors
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.

Details

For each pair of conditions, compute the fraction of effects that are within a factor 'factor' of one another. The results are returned as an R by R matrix.

Examples

simdata = simple_sims(50,5,1)
data = mash_set_data(simdata$Bhat, simdata$Shat)
m = mash(data, cov_canonical(data), posterior_samples=5, algorithm='R')
get_pairwise_sharing_from_samples(m) # sharing by magnitude (same sign)
get_pairwise_sharing_from_samples(m, factor=0) # sharing by sign
get_pairwise_sharing_from_samples(m, FUN=abs) # sharing by magnitude when sign is ignored

mashr documentation built on Oct. 18, 2023, 5:08 p.m.