QIIME-1.9.1 in Discovery Environment

Owned by upendra kumar Devisetty
Last updated: Apr 12, 2016
4 min read
Alert:

 

The iPlant App Store is currently being restructured, and apps are being moved to an HPC environment. During this transition, users may occasionally be unable to locate or use apps that are listed in our tutorials. In many cases, these apps can be located by searching them using the search bar at the top of the Apps window in the DE. To increase the chance for search success, try not searching the entire app name and version number but only the portion that refers to the app's function or origin (e.g. 'SOAPdenovo' instead of 'SOAPdenovo-Trans 1.01'). In critical cases, please report your concern to the iPlant Ask forum or to support@iplantcollaborative.org. Thank you for your patience.

The DE Quick Start tutorial provides an introduction to basic DE functionality and navigation. Please work through the tutorial and add your comments on the bottom of this page. Or send comments per email to upendra@cyverse.org. Thank you.

Rationale and background:


QIIME (canonically pronounced chime): Quantitative Insights Into Microbial Ecology (http://www.qiime.org)

J Gregory Caporaso, Justin Kuczynski, Jesse Stombaugh, Kyle Bittinger, Frederic D Bushman, Elizabeth K Costello, Noah Fierer, Antonio Gonzalez Pena, Julia K Goodrich, Jeffrey I Gordon, Gavin A Huttley, Scott T Kelley, Dan Knights, Jeremy E Koenig, Ruth E Ley, Catherine A Lozupone, Daniel McDonald, Brian D Muegge, Meg Pirrung, Jens Reeder, Joel R Sevinsky, Peter J Turnbaugh, William A Walters, Jeremy Widmann, Tanya Yatsunenko, Jesse Zaneveld and Rob Knight; Nature Methods, 2010; doi:10.1038/nmeth.f.303


QIIME is an open-source bioinformatics pipeline for performing microbiome analysis from raw DNA sequencing data. QIIME is designed to take users from raw sequencing data generated on the Illumina or other platforms through publication quality graphics and statistics. This includes demultiplexing and quality filtering, OTU picking, taxonomic assignment, and phylogenetic reconstruction, and diversity analyses and visualizations. QIIME has been applied to studies based on billions of sequences from tens of thousands of samples.

DE apps for QIIME analyses

  1. qiime1.9.1-validate_mapping_file (DE app for checking the user's metadata mapping file for required data, valid format and report errors): 

           Input(s):

    1. Mandatory arguments
      -  Mapping file 

    2. Optional arguments
      - Output folder name (default is "vmf-map")

          Output:

           A log file, html file, and corrected_mapping.txt file.


2. qiime1.9.1-split_libraries_fastq (DE app for demultiplexing and quality filtering sequences):

            Input(s):

    1. Mandatory arguments
      - The sequence read fastq file (can be gzipped)

      - Output folder name (default is "slout")

    2. Optional arguments

      - Mapping file

      - Barcode fastq file (can be gzipped)

      - Phred quality score (default is "3")

      - Barcode type (default is "golay_12")

           Output:

           Demultiplexed and quality filtered Illumina fastq data and written results to ./slout (default) directory

 

       3. qiime1.9.1-count_seqs (DE app for counting the number of sequences in fasta file)

           Input(s):

                 a. Mandatory arguments

                     - The sequence read fastq file (can be gzipped)

                b. Optional arguments

                    - Output file (default is "output.txt")

            Output:

                      Count the sequences in a fasta file and write results to output.txt file (default).



         4. qiime1.9.1-pick_open_reference_otus (DE app for performing open-reference OTU picking)

             Input(s):

a. Mandatory arguments

            - The input sequences in fasta file 

             - The output directory (default is "otus")

             Output:

                      The primary output that we get from this command is the OTU table, or the number of times each operational taxonomic unit (OTU) is observed in each sample.

 
       
        5. qiime1.9.1-core_diversity_analyses (DE app for running core set of QIIME diversity analyses)

           Input(s):

    a. Mandatory arguments
        - The input biom file 
        - Output directory (default is "cdout") 
        - Mapping file
        - Sequencing depth (to use for even sub-sampling and maximum rarefaction depth. You should review the output of the ‘biom summarize-table’ command to decide on this value).

   b. Optional arguments
        - Path to the tree file (if one should be used. Required unless –nonphylogenetic_diversity is passed. [default: no tree will be used])

   Output:
           The results above treat all samples independently, but sometimes (for example, in the taxonomic summaries) it's useful to categorize samples by their metadata

6. qiime1.9.1-make_emperor (DE app for making 3D PCoA plots)
           
     Input(s):

     a. Mandatory arguments
         - The input coordinates file
         - Mapping file

     b. Optional arguments
         - Output folder name (default is "emperor")
         - Custom axes (Comma-separated list of metadata categories to use as custom axes in the plot).

    Output:
          The 3D PCoA plots are written to ./emperor (default) folder.

Test/Sample data: 

The following test data are provided for testing QUAST in here : /iplant/home/shared/iplantcollaborative/example_data/QIIME.sample.data

  1. illumina (folder)
    1. Mapping files (map.tsv and map-bad.tsv)
    2. Fastq file (forward_reads.fastq.gz)
    3. Barcode fastq file (barcodes.fastq.gz)
    4. Precomputed output folder (precomputed-output)

  2. Parameters file (uc_fast_params.txt)