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i'm intuiting a bit, but i think the periodic kernel could be appropriate for tissues where there are repeating spatial patterns e.g., the pancreas, colon, etc. instead of well-defined, non-repeating patterns like the brain. the periodic kernel is defined as:
where $p$ is the period of the kernel and $\ell$ is the length-scale of the approximate GP. this can be easily pre-computed in R and then passed to Stan.
good values of $p$ depend on the resolution of the spatial dataset i.e., roughly equal to the typical inter-spot distance or perhaps a small multiple of it. ergo, the default should be maybe $50-100$, though the user should really set this parameter since spatial resolution varies wildly between technologies.
The text was updated successfully, but these errors were encountered:
i'm intuiting a bit, but i think the periodic kernel could be appropriate for tissues where there are repeating spatial patterns e.g., the pancreas, colon, etc. instead of well-defined, non-repeating patterns like the brain. the periodic kernel is defined as:
where$p$ is the period of the kernel and $\ell$ is the length-scale of the approximate GP. this can be easily pre-computed in R and then passed to Stan.
good values of$p$ depend on the resolution of the spatial dataset i.e., roughly equal to the typical inter-spot distance or perhaps a small multiple of it. ergo, the default should be maybe $50-100$ , though the user should really set this parameter since spatial resolution varies wildly between technologies.
The text was updated successfully, but these errors were encountered: