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Hello,
Is there some guidance on when to use the non-default ("k-distance") option for the fdr.weighting parameter in the testNhoods() function? In the "Making comparisons for differential abundance using contrasts" vignette, the fdr.weighting parameter for the testNhoods() function is set to "graph-overlap", but it's not clear why this is chosen.
Thank you,
Peter Bazeley
The text was updated successfully, but these errors were encountered:
Reading the issues, it seems like the k-distance is an older and much slower approach.
#99 and #249 have some details on this, but that's my read at least. I've used both on some datasets, and haven't really observed a difference in results, except the fact that k-distance takes ~15 mins on my dataset while graph overlap was seconds.
Hello,
Is there some guidance on when to use the non-default ("k-distance") option for the fdr.weighting parameter in the testNhoods() function? In the "Making comparisons for differential abundance using contrasts" vignette, the fdr.weighting parameter for the testNhoods() function is set to "graph-overlap", but it's not clear why this is chosen.
Thank you,
Peter Bazeley
The text was updated successfully, but these errors were encountered: