Distribution-based OTU calling
Project description
dbotu3 is a new implementation of Sarah Preheim’s dbOTU algorithm. The scope is narrower, the numerical comparisons are faster, and the interface is more user-friendly.
Read the documentation for:
a guide to getting started,
an explanation of the algorithm, and
the API reference.
You can also read our new paper for more technical details about the algorithm. The Alm Lab website also has a short page with information.
Installation
dbotu3 is also on conda and can be installed as follows:
conda install -c cduvallet -c conda-forge dbotuFor QIIME 2 users, dbotu3 is also available as a plugin.
The PyPi package is no longer update.
Requirements
Version history
1.1: Corrected error where sequence IDs that could be read as integers would not be found in the table
1.2: Python 2 compatibility, tox test framework, warnings for improperly-formatted sequence count tables
1.2.1: Added setup requirements
1.3.0: Improved OTU file header. Split the log file into a debug and progress log.
1.4.0: Made an improvement to the Levenshtein-based genetic dissimilarity metric.
1.4.1: Account for pandas API change to MultiIndex
1.5.0: Added the restart and rep seq scripts
1.5.1: New function for Qiime2 compatibility
1.5.2: Move files around to make this a Python package (rather than dbotu.py script)
1.5.3: Point to conda, rather than PyPi, installation
To-do
Testing for the restart scripts
Better coverage for unit tests
Citation
If you use dbOTU3 in a scientific paper, we ask that you cite the original dbOTU publication (Preheim et al.) or the dbOTU3 publication:
Preheim et al. Distribution-Based Clustering: Using Ecology To Refine the Operational Taxonomic Unit. Appl Environ Microbiol (2013) doi:10.1128/AEM.00342-13.
Olesen SW, Duvallet C, and Alm EJ. dbOTU3: A new implementation of distribution-based OTU calling. PLoS ONE (2017) doi:10.1371/journal.pone.0176335.
