Memory Error with Clustering with Leiden algorithm matrix - When to use matrix vs igraph method? about leidenalg

[TomKellyGenetics]

My opinion: maybe it's time to use igraph directly.
https://igraph.org/r/doc/cluster_leiden.html

@SamGG the leiden package already does this by default for igraph objects, although limited parameters are supported compared to calling Python. This has been supported for over a year with the 0.4 version.

maybe it has to do with inefficient transfer of data between R and Python

@szhorvat that’s correct it does (reticulate supports dense matrices but not sparse matrices or igraph objects so igraph objects are passed as an edge list and recreated in Python). This only applies to older versions of the R package for the reasons discussed above so the comment in Seurat documentation is likely no longer relevant for users running igraph 1.2.7 and leiden 0.4.0 or later.

[szhorvat]

Presumably yes. But you need to discuss this with the packages that implemented these methods. This choice of methods does not come from the leidenalg Python package.

[denvercal1234]

Thanks Szabolcs. Hopefully someone from Seurat will give some input.

[szhorvat]

Using a matrix is not a feature of this library. It is entirely specific to the leiden R package, which will convert that matrix to a graph before doing any community detection.

Given what the leiden package does, the claim in Seurat's documentation that the "matrix" method is faster for small data seems rather strange ... maybe it has to do with inefficient transfer of data between R and Python.

[denvercal1234]

Thanks @szhorvat -- just so I understand it correctly, did you mean specifying method="matrix" or method="igraph" does not really impact the resulting clusters but it is simply helpful for efficiency of how the data is processed before community detection? For example, with large dataset, specifying method=igraph will skip the conversion of the data to a dense matrix, thereby speeding up the whole clustering (community detection).

[SamGG]

Probably @TomKellyGenetics could bring some clues.

My opinion: maybe it's time to use igraph directly.
https://igraph.org/r/doc/cluster_leiden.html

[SamGG]

Thanks for this information and your feedback.

[vtraag]

Thanks all for commenting in my absence! I believe all questions are addressed, so I'm closing this.