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Resource Name
HPC-CLUST
RRID:SCR_005052 RRID Copied      
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HPC-CLUST (RRID:SCR_005052)
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Resource Information

URL: http://meringlab.org/software/hpc-clust/

Proper Citation: HPC-CLUST (RRID:SCR_005052)

Description: A set of tools designed to cluster large numbers (>1 million) of pre-aligned nucleotide sequences. It performs the clustering of sequences using the Hierarchical Clustering Algorithm (HCA). There are currently three different cluster metrics implemented: single-linkage, complete-linkage, and average-linkage. In addition, there are currently four sequence distance functions implemented, these are: identity (gap-gap counting as match), nogap (gap-gap being ignored), nogap-single (like nogap, but consecutive gap-nogap''s count as a single mismatch), tamura (distance is calculated with the knowledge that transitions are more likely than transversions). One advantage that HCA has over other algorithms is that instead of producing only the clustering at a given threshold, it produces the set of merges occuring at each threshold. With this approach, the clusters can afterwards very quickly be reported for every arbitrary threshold with little extra computation. This approach also allows the plotting of the variation of number of clusters with clustering threshold without requiring the clustering to be run for each threshold independently. Another feature of the way HPC-CLUST is implemented is that the single-, complete-, and average-linkage clusterings can be computed in a single run with little overhead.

Abbreviations: HPC-CLUST

Resource Type: software resource

Defining Citation: PMID:24215029

Keywords: c++, mpi

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University of Zurich; Zurich; Switzerland

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