QIIME

QIIME (pronounced chime) stands for Quantitative Insights Into Microbial Ecology, 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 Illumina or other platforms to publication-quality graphics and statistics. This includes demultiplexing and quality filtering, OTU picking, taxonomic assignment, phylogenetic reconstruction, diversity analyses and visualizations. QIIME has been applied to studies based on billions of sequences from tens of thousands of samples.

Note: QIIME 2 has replaced QIIME 1 as of January 1, 2018; version 1 is no longer supported.

Note: As of February, 2020, due to various issues generated by Conda environments in our HPC systems, installation using Anaconda or Miniconda is no longer supported.

Installation

QIIME2 can be installed using Singularity or using EasyBuild. Singularity is strongly preferred since it does not generate many thousands of files in your home directory, potentially causing you to exceed the disk quota limit on the number of files.

Using Singularity

The QIIME2 developers publish images on Docker Hub. In order to use one of these images on our systems you must first build a Singularity image:

[name@server ~]$ module load singularity
[name@server ~]$ singularity build qiime2-2019.10.sif docker://qiime2/core:2019.10

This build step may take over an hour, but you only need do this once. Save the image file (qiime2-2019.10.sif in this example) for later re-use.

Then run your code as described at Singularity. Typically you will run each QIIME command in a singularity exec statement:

[name@server ~]$ singularity exec qiime2-2019.10.sif <your QIIME command>

So your SBATCH script might look something like this:

#!/bin/bash
#SBATCH --time=15:00:00
#SBATCH --account=def-someuser

singularity exec -B /home -B /project -B /scratch qiime2-2019.10.sif \
  qiime tools import \
  --type 'FeatureData[Sequence]' \
  --input-path /path/to/some_fastafile.fa \
  --output-path /path/to/some_output_feature.qza

singularity exec -B /home -B /project -B /scratch qiime2-2019.10.sif \
  qiime tools import \
  --type 'FeatureData[Taxonomy]' \
  --input-format HeaderlessTSVTaxonomyFormat \
  --input-path /path/to/some_taxonomy_file.tax \
  --output-path /path/to/some_output_ref-taxonomy.qza

singularity exec -B /home -B /project -B /scratch qiime2-2019.10.sif \
  qiime feature-classifier fit-classifier-naive-bayes \
  --i-reference-reads  /path/to/some_output_feature.qza \
  --i-reference-taxonomy /path/to/some_output_ref-taxonomy.qza \
  --o-classifier /path/to/some_output_classifier.qza

Note that it is important to bind the folders you want to work with to the execution of the container. For more information about Singularity, you can watch the recorded Singularity webinar.

On first importing data into QIIME format you may receive an error ending with a message like this:

Timezone offset does not match system offset: 0 != -18000. Please, check your config files.

This can be worked around by setting a time zone before invoking Singularity:

[name@server ~]$ export TZ='UTC'
[name@server ~]$ singularity exec qiime2-2019.10.sif qiime tools import ...

Using an EasyBuild wheel

In case the Singularity solution isn't working for you, we also provide an EasyBuild package that can be used with the eb command. To install version 2019.7, use

[name@server ~]$ eb --rebuild Miniconda3-4.7.10.eb QIIME2-2019.7.eb

This takes a while, but will provide you with the qiime/2019.7 module that you need to load before using QIIME 2.

[name@server ~]$ module load qiime2/2019.7

Because this creates all the packages required for QIIME, it generates too many files in your home directory. We recommend that you remove those files once you are done with all computations since it uses almost half of your total allocation. The Singularity solution described above creates one big file instead of thousand of smaller files, which is why we recommend it.

References

QIIME homepage
EasyBuild documentation