Comments (6)
Hej og mange tak! I hope it's useful for your work! do let me know if you run into any issues and I'll be happy to help
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hi, thanks for your very kind messages. Please let me know if you need any pointers on tuning the params.
cheers
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@SansMorel how do you think of this method, I am always focusing on the clustering method on a large dataset, besides the DL method.
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@chenxofhit I have large CyTOF datasets that I cluster. I have tried several other methods, such as k-means, phenograph, x-shift, leiden, FlowSOM, but they all have drawbacks (mainly being very slow or unable to capture subpopulations). For my data sets, graph based methods have proven most accurate, as they are able to capture subpopulations, but then you get into the issue of overfragmentation when choosing the correct k and they also tend to be slow very slow. Parc, however, has been able to make a very good compromise in this area.
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@SansMorel Thanks for your sharing your experience with this method. The method it really takes advantage of the first step, which is really tricky at the first glance. Thanks for @ShobiStassen contributing this excellent method.
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Brilliant work. One of the smoothest new methods that worked in the first try. Well done @ShobiStassen If I were you, I will talk with Alex to get it integrated into Scanpy for more visibility and generally for the benefit of the community. All the best.
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Related Issues (20)
- any plan to release an R version of PARC? HOT 4
- Tips for replicating the performance on the lung cell clustering HOT 3
- Relaxation of leidenalg==0.7.0 requirement? HOT 2
- About the true labels for calculating the F1 scores HOT 2
- Error when running UMAP HOT 3
- Question on pruning big cluster HOT 2
- Python igraph HOT 4
- Hello! I am getting AttributeError, when trying to import parc HOT 2
- RStudio crashing when clustering a large dataset HOT 12
- Questions on using PARC for identifying plasma cells HOT 1
- Hyperclustering with PARC HOT 1
- Import of umap increases PARC import time HOT 1
- Minor bug in run_toobig_subPARC
- `run_umap_hnsw` doesn't work
- pip install issue: Mac OS X and AWS Linux HOT 3
- np.reshape error if too many edges are pruned HOT 1
- Example Usage 2 has some code typos HOT 2
- Bugs in Example Usage 3 HOT 2
- Controlling the number of clusters HOT 4
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