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
```

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

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.