GitHub - mgtools/AbundantOTU (original) (raw)

Program Name: AbundantOTU+ (AbundantOTU with additional functions)

Most recent release: 0.95b

• Released on Feb 1, 2019
• Developer: Yuzhen Ye yye@indiana.edu
• Affiliation: School of Informatics and Computing, Indiana University, Bloomington
• The development of AbundantOTU was supported by NIH grants 1R01HG004908 & 1U01HL098960
• AbundantOTU+ is free software under the terms of the GNU General Public License as published by the Free Software Foundation.

Releases

• What's new in AbundantOTU+0.95b
  • Add support for paired reads (using -i read1-file -j read2-file)
  • Add scripts (under scripts folder) for processing multiple samples to output an OTU-sample table
  • Add example files (under msample folder) to demonstrate the steps from multiple samples to OTU-sample table
• What's new in AbundantOTU+0.93b (Feb 10, 2013)
  • Bugs fixed--a couple of variables were not initialized properly, which may result in differnet results on different machines of the same dataset.
• What's new in AbundantOTU+0.92b (Jan 10, 2012)
  • AbundantOTU+0.92b fixed a few bugs
  • Added option: -abundantonly If you specify -abundantonly, AbundantOTU+ will stop after the consensus alignment step (for inference of abundant species) without attemping the heuristic step to group the rare sequences -- making AbundantOTU+ equivalent to AbundantOTU. When to use -abundantonly:
    1. you only care about abundant OTU
    2. you have been using AbundantOTU2.0 and felt it is just right for you
    3. to speedup the calculation--because the last step is skipped
• What's new in AbundantOTU+ (Jan 25, 2011)
  • AbundantOTU+ works to infer abundant OTUs (using consensus alignment algorithm) and rare OTUs (using heuristic strategy)
• Notes before you start
  • AbundantOTU+ was tested extensively on linux computers. It should work on linux and unix machines.
  • How much memory will AbundantOTU+ consume? It uses about 1.5 of the size of the input sequence file (or less).

Introduction

AbundantOTU+ is a tool for fast identification and quantification of abundant Operational Taxonomic Units (OTU). It takes in DNA sequences of 16S rRNA genes (gene fragments) as inputs, and outputs consensus sequences of abundant OTUs.

AbundantOTU+ (and AbundantOTU) on the web:http://omics.informatics.indiana.edu/AbundantOTU(Please check the project home page for updates and newer version of the program)

Installation

Simply run install

The executable file "AbundantOTU" will be created under folder bin/

Using AbundantOTU+

Usage: type AbundantOTU+ for usages

See an example under examples/, go to this folder, and run,

  ../bin/AbundantOTU+ -i DivergentGSFLXClean.fa -o DivergentGSFLXClean-AbundantOTU+

  Input: DivergentGSFLXClean.fa
  Outputs:
   DivergentGSFLXClean-AbundantOTU.cons      -- a file of consensus sequences, each representing an abundant OTU
   DivergentGSFLXClean-AbundantOTU.clustsize -- a file of the sizes of the OTUs
   DivergentGSFLXClean-AbundantOTU.clust     -- a file of detailed information of the recruitment of the reads

  Note: there is no more *.single files produced by AbundantOTU+ (unless you use -abundantonly option);
        but you may decide the abundant level of the OTUs you are interested by checking the *.clustsize file

Using AbundantOTU+ for multiple samples

• Check msample/readme for details; example files can also be found in msample folder.
• Note that you can change parameters when calling otu-sample-table.py to produce the OTU-sample table according to your need.
• Examples, "-m 5" to change minimum read suppport (5) for the OTUs to be included in the table; "-n no" to output read counts (instead of proportions) in the table.

Notes

• If AbundantOTU+ claims that there are many sequences with multiple seeds, if means that many of your sequences contain repeats. One possibility is that you forgot to trim your sequences--they contain identical tags at both ends of the sequences.

Citation

• Yuzhen Ye, Fast and accurate identification and quantification of abundant species from pyrosequences of 16S rRNA by consensus alignment. The Proceedings of BIBM 2010, 153-157