Detect a "shift of mass" between two conditions. For example expression might move later in a time series in an experimental condition vs a control. If all expression shifted to a later time in the experimental condition, this would be given an effect size of 1. Conversely if all expression shifted to an earlier time, the effect size would be -1.

effect_shift(coef1, coef2) effect_shift_stepdown(coef1, coef2) effect_shift_stepup(coef1, coef2) effect_shift_log2(coef1, coef2) effect_shift_stepdown_log2(coef1, coef2) effect_shift_stepup_log2(coef1, coef2)

coef1 | Column numbers in the design matrix for the first condition, in some meaningful order. |
---|---|

coef2 | Corresponding column numbers for the second condition. |

An object defining how to calculate an effect size.

This can be viewed as similar to Somers' D.
`effect_shift_log2`

is adapted to work with log2 scaled coefficients. This is almost certainly the version you want.

Note that this effect size is not symmetric: `effect_shift_log2(c(1,2),c(3,4))`

and `effect_shift_log2(c(1,3),c(2,4))`

will give different results.

The _stepdown and _stepup versions are for cumulative distributions. These are most useful in group effect form, where they can be used to examine shifts in start or end of transcriptions from RNA-seq or microarray data.