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JinmiaoChenLab / Rphenograph

Rphenograph: R implementation of the PhenoGraph algorithm
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Unclustered data #3

Closed anirudhpatir closed 6 years ago

anirudhpatir commented 6 years ago

Hi,

Have enjoyed using your package, just had an issue with cases where samples remain unclustered.

On using lower values of k, some data remains unclustered. Is it possible to add these to the output membership (unconnected components of the graph), as currently these are removed from the final output and it's difficult to retrace which samples these are.

Thank you

funa1019 commented 4 years ago

hi I have the same problem.....so sad

SamGG commented 4 years ago

Hi, I am not the developer, but a frequent user. I never came to such a problem, but I didn't check the output it in fact. I am curious about how some samples are not reported. If you could share your dataset or a toy example, that would be nice. Those samples could be identified using setdiff function I think. Try something like:

unclustered_ids = setdiff(seq(nrow(my_dataset)), as.numeric(names(membership(my_rphenograph_result[[2]]))))

Let me know.