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CLUSTOM-CLOUD: In-Memory Data Grid-Based Software for Clustering 16S rRNA Sequence Data in the Cloud Environment

Fig 2

Schematic diagram of clustering workflow.

16S rRNA sequences in FASTA format are provided as input. Each input file, already checked for low-quality and chimera errors, is pre-processed by the removal of duplicates and transformation of k-mer into numeric values. A fixed number of sequence pairs are distributed to each cluster node for k-mer (initial) and NW (refinement) distance calculation. Processed results are merged upon completion of each unit task. Clusters are determined based on criteria described previously [11] and in text. Output files are created and data are cleared from memory.

Fig 2

doi: https://doi.org/10.1371/journal.pone.0151064.g002