QIIME

Description

qiime website  

QIIME (pronounced "chime") stands for Quantitative Insights Into Microbial Ecology. QIIME is an open source software package for comparison and analysis of microbial communities, primarily based on high-throughput amplicon sequencing data (such as SSU rRNA) generated on a variety of platforms, but also supporting analysis of other types of data (such as shotgun metagenomic data). QIIME takes users from their raw sequencing output through initial analyses such as OTU picking, taxonomic assignment, and construction of phylogenetic trees from representative sequences of OTUs, and through downstream statistical analysis, visualization, and production of publication-quality graphics. QIIME has been applied to single studies based on billions of sequences from thousands of samples.

Environment Modules

Run module spider qiime to find out what environment modules are available for this application.

System Variables

• HPC_QIIME_DIR - installation directory

How To Run

• TMPDIR

QIIME will use /tmp by default, which will fill up memory disks on HPG2 nodes and cause node and job failures. Our qiime modules will automatically create a 'tmp' directory inside the current working directory and set the variable TMPDIR to point to it. The tmp directory will be removed on the qiime module unload.

• Tasks vs Cores for parallel runs

Python threads in a parallel QIIME job will be bound to the same CPU core even if multiple ntasks are specified in the job script. Use cpus-per-task to parallelize QIIME jobs correctly. For example, for an 8-thread parallel QIIME job use the following resource request in your job script:

#SBATCH --ntasks=1
#SBATCH --cpus-per-task=8

See the single-threaded and multi-threaded examples on the Sample SLURM Scripts page for more details.

Citation

If you publish research that uses qiime you have to cite it as follows:

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