Difference between revisions of "Applications/Crop"

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==Usage==
 
==Usage==
  
CROP, which stands for "Clustering 16s rRNA for OTU Prediction", is a software developed in Ting Chen's Lab at University of Southern California in 2011 by Haoxiao Lin, Rui Jiang and Ting Chen.
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CROP, which stands for "Clustering 16s rRNA for OTU Prediction", is a software developed in Ting Chen's Lab at the University of Southern California in 2011 by Haoxiao Lin, Rui Jiang and Ting Chen.
  
 
CROP is an unsupervised nucleic acid sequence clustering algorithm. The algorithm sees the OTUs as a Gaussian mixture and models the clustering process using Birth-death MCMC. This approach makes the OTU prediction more accurate.
 
CROP is an unsupervised nucleic acid sequence clustering algorithm. The algorithm sees the OTUs as a Gaussian mixture and models the clustering process using Birth-death MCMC. This approach makes the OTU prediction more accurate.
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</pre>
 
</pre>
  
See https://github.com/tingchenlab/CROP/blob/master/CROP%20User's%20Guide%20v1.33.pdf for further details on options used.
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See https://github.com/tingchenlab/CROP/blob/master/CROP%20User's%20Guide%20v1.33.pdf for further details on the options used.
  
  
==Further Information==
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==Next Steps==
  
 
* [https://github.com/tingchenlab/CROP https://github.com/tingchenlab/CROP]
 
* [https://github.com/tingchenlab/CROP https://github.com/tingchenlab/CROP]

Revision as of 16:52, 8 November 2022

Application Details

  • Description:
  • Version: 1.33 (compiled with gcc-6.3.0)
  • Module: crop/1.33/gcc-6.3.0
  • Licence: GNU

Usage

CROP, which stands for "Clustering 16s rRNA for OTU Prediction", is a software developed in Ting Chen's Lab at the University of Southern California in 2011 by Haoxiao Lin, Rui Jiang and Ting Chen.

CROP is an unsupervised nucleic acid sequence clustering algorithm. The algorithm sees the OTUs as a Gaussian mixture and models the clustering process using Birth-death MCMC. This approach makes the OTU prediction more accurate.

To know more about the theoretical basis of CROP, please refer to the following paper: Clustering 16S rRNA for OTU prediction: a method of unsupervised Bayesian clustering, Bioinformatics (2011)

Module


[username@login01 ~]$ module add crop/1.33/gcc-6.3.0
[username@login01 ~]$ CROPLinux –i MyInput.fasta

See https://github.com/tingchenlab/CROP/blob/master/CROP%20User's%20Guide%20v1.33.pdf for further details on the options used.


Next Steps


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