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IMB-Computational-Genomics-Lab / ascend

R package - Analysis of Single Cell Expression, Normalisation and Differential expression (ascend)
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Clustering options #15

Closed asenabouth closed 5 years ago

asenabouth commented 6 years ago

As requested by @MichaelPeibo in #14:

besides, does Ascend has any options which can be used to cluster 'once for all' or tune the 'cluster resolution' like Seurat did, rather than, repeated clustering?

As of version 0.3, ascend has a resolution tuning option (nres) :

clustered.set <- RunCORE(em.set, nres = 50)

This allows users to select the number of resolutions to use to determine the optimal resolution. The number of resolutions users can choose must be between 20 and 100.

The CORE algorithm can be considered a 'once for all' method, in which it generates a series of results and selects the best one. If you are not satisfied with the result, you can refer to the other results with the data frame available through the GetRandMatrix function.

MichaelPeibo commented 6 years ago

Thanks Anne , I will explore more by tuning parameters; Looking forward to new add-ons!