CROP statistics

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CROP specifications


Unique identifier OMICS_01442
Alternative name Clustering 16S rRNA for OTU Prediction
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Windows
Programming languages C++
License GNU General Public License version 2.0
Computer skills Advanced
Stability Stable
Maintained Yes


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Publication for Clustering 16S rRNA for OTU Prediction

CROP in publications

PMCID: 5180584
PMID: 28028473
DOI: 10.7717/peerj.2807

[…] ) and no remaining chimeric sequences were found., the sequences were clustered into molecular operational taxonomic units (motus) using the bayesian clustering algorithm implemented in crop (clustering 16s rrna for otu prediction, ). this method uses a gaussian mixture model to infer the optimal clustering of the data without setting a single fixed similarity threshold for all clusters. […]

PMCID: 3742672
PMID: 23967117
DOI: 10.1371/journal.pone.0070837

[…] . lastly, to avoid using a hard threshold value in clustering as implemented in hierarchical and heuristic methods, hao et al proposed a gaussian mixture model-based clustering algorithm termed clustering 16s rrna for otu prediction (crop). it adopts an unsupervised probabilistic bayesian clustering algorithm and uses a soft threshold for defining otus. the crop algorithm bypasses setting […]

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CROP institution(s)
Molecular and Computational Biology Program, Department of Biology, University of Southern California, Los Angeles, CA, USA; MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST/Department of Automation, Tsinghua University, Beijing, China
CROP funding source(s)
National Institutes of Health; Center of Excellence in Genomic Sciences (CEGS) 2P50 HG002790-06; National Science Foundation of China (60805010)

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