Open kiddo18 opened 1 year ago
MAUDE assumes the data are approximately normally distributed. That said, it seems to work pretty well even when it is not. Your case is a little weird because you're taking two corners of a distribution and there is no way you can rotate the data to make the ++ and -- bins correspond to tails of the distribution. It will probably still work, but the effect sizes will be off (their relative values should still be meaningful). I think the statistics (P-values, FDR, stoufferZ) will all be fine since they are calibrated with the negative control guides. I would be interested to know if it works for you.
Ah interesting point
I just wonder if MAUDE can somehow be adapted such that it assumes a 2D Gaussian (or even n-d Gaussian) instead
But thank you for your input! I'll try it out and follow up later
Had you done 4 bins (e.g. GFP high and low, and separately BFP high and low), you could analyze them separately and then find elements that are high in both or low in both (also high in one and low in the other, etc). With only ++ and --, I don't think you can estimate the separate effects on GFP and BFP (as in a 2D gaussian). With all 4 corners there is probably a way, and that would probably be best (with 4 bins), but MAUDE would require modification for this use case. Best of luck!
Hi Dr De Boer,
I know MAUDE was designed for single-reporter screen (eg GFP-high vs GFP-low), but just wondering if I can use MAUDE for two-reporter screen (eg GFP-high/BFP-high vs. GFP-low/BFP-low) as well?
If yes, should I make any change to the inputs as indicated in your paper?