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

In Alice-MacQueen/CDBNgenomics: Genomics Using the Cooperative Dry Bean Nursery Dataset

Description

Compute the proportion of (significant) signals shared by magnitude in each pair of conditions, based on the poterior mean

Usage

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

Arguments

m	the mash fit
factor	a number between 0 and 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 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.

Examples

## Not run: 
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

## End(Not run)

Alice-MacQueen/CDBNgenomics documentation built on Aug. 18, 2020, 4:39 p.m.