differential accessibility- direction, magnitude, and contrasts question

[DoaneAS]

Hi,

For the differential accessibility function, diff_acc <- differentialDeviations(dev, "Cell_Type") the output returns a data frame of p-values, but the direction is not clear to me. Is there a method to extract the magnitude and direction of change, along the lines of z-score or log fold change?

Also, when computing the difference between groups, how do we specify the groups being compared, especially in cases where there are more than 2 groups (i.e. is it possible to specify a contrast?).

thanks

[DoaneAS]

Also wonder if you could provide any insight into the distribution of p-values returned. deff_dev.qqplot.pdf

[AliciaSchep]

In response to your questions:

Seems like it would be useful for the function to return some magnitude of change! I generally find the difference between the mean of the groups using the result of computeDevitations, but I can see that it would be nice to include this in the function output. I'll try to add that sometime soonish.

For multiple groups, an ANOVA test is performed. I agree it would be nice to be able to specify contrast, but the function as is was intended to be pretty basic, as the matrix of bias corrected deviations can be passed on to other functions & packages for additional downstream analysis.

As for the distribution you shared, don't have much insight! looks strange, but without knowing anything about the data that went in don't really have much to add. E.g. how was the 'parametric' option, is this with single cell or bulk (how many samples), two groups or more than two.

[kmothera]

Hi @AliciaSchep,

I'd like to resurrect this old thread to ask a question on how actually calculate that fold change? There are two "assays" stored within the results of computeDeviations: "deviations" and "z". Which of these would you recommend to calculate a fold change?

Is it FC= avg(Treatment) - avg(Control) of the z scores?

Thank you!