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Hi guys, thanks a lot for developing this package! I use it in my work pretty much daily.
I've been looking into different measures of how spatially clustered points can be, and decided to use your squidpy.gr.ripley function. However, after reading the book you cite ([Baddeley et al., 2015]) I can see that the authors recommend including some edge correction method to account for the points that are near the area edges and therefore might show a distorted clustering pattern which then will influence the plot and its assessment. I had a quick look at your code for the function and I believe you have not implemented any methods for edge correction. If this is correct, do you plan to do so?
Thanks!
The text was updated successfully, but these errors were encountered:
hi @zsfrbkv , thank you for the interest and the appreciation!
You raised a very important point, and indeed we don't do edge-correction for the ripley functions. We currently do not plan to do so, but if you are interested in contributing, I'd be happy to support it! Is there any edge-correction method that you would recommend and is suitable to spatial omics data?
Hi guys, thanks a lot for developing this package! I use it in my work pretty much daily.
I've been looking into different measures of how spatially clustered points can be, and decided to use your
squidpy.gr.ripley
function. However, after reading the book you cite ([Baddeley et al., 2015]) I can see that the authors recommend including some edge correction method to account for the points that are near the area edges and therefore might show a distorted clustering pattern which then will influence the plot and its assessment. I had a quick look at your code for the function and I believe you have not implemented any methods for edge correction. If this is correct, do you plan to do so?Thanks!
The text was updated successfully, but these errors were encountered: