QIIME/fr: Difference between revisions
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'''QIIME''' (pronounced ''chime'') stands for ''Quantitative Insights Into [https://en.wikipedia.org/wiki/Microbial_ecology Microbial Ecology]'', is an open-source [https://en.wikipedia.org/wiki/Bioinformatics bioinformatics] pipeline for performing [https://en.wikipedia.org/wiki/Microbiota microbiome] analysis from raw DNA sequencing data. QIIME is designed to take users from raw sequencing data generated on [https://www.illumina.com/ Illumina] or other platforms to publication-quality graphics and statistics. This includes demultiplexing and quality filtering, [https://en.wikipedia.org/wiki/Operational_taxonomic_unit 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. | '''QIIME''' (pronounced ''chime'') stands for ''Quantitative Insights Into [https://en.wikipedia.org/wiki/Microbial_ecology Microbial Ecology]'', is an open-source [https://en.wikipedia.org/wiki/Bioinformatics bioinformatics] pipeline for performing [https://en.wikipedia.org/wiki/Microbiota microbiome] analysis from raw DNA sequencing data. QIIME is designed to take users from raw sequencing data generated on [https://www.illumina.com/ Illumina] or other platforms to publication-quality graphics and statistics. This includes demultiplexing and quality filtering, [https://en.wikipedia.org/wiki/Operational_taxonomic_unit 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''' : Le 1er janvier 2018, QIIME 2 a remplacé QIIME 1 qui est depuis obsolète. | ||
==Installation == | ==Installation == | ||
Revision as of 14:30, 8 February 2020
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 : Le 1er janvier 2018, QIIME 2 a remplacé QIIME 1 qui est depuis obsolète.
Installation
QIIME 2 can be installed in your home directory using conda. It is not possible to install this software using pip at this time.
The installation procedure depends on whether or not you have a conda environment.
With a conda environment
Although we do not recommend using conda environments in an HPC environment, we provide the option to do so at your own peril.
General installation instructions by the QIIME 2 developers are found here. Instructions adapted for Compute Canada systems are given here for version 2019.7. If a new version of the .yml file is released (check the link), use the newer version by updating the instructions below.
eb Miniconda3-4.5.12.eb module load miniconda3 conda update conda wget https://data.qiime2.org/distro/core/qiime2-2019.7-py36-linux-conda.yml conda env create -n qiime2-2019.7 --file qiime2-2019.7-py36-linux-conda.yml conda init bash conda activate qiime2-2019.7
Remember to log out and log back in after the "conda init bash" step.
To run QIIME 2, use
module load miniconda3 conda activate qiime2-2019.7
Without a conda environment (preferred)
Since we know that conda environments can create more problems that they solve in HPC systems, we provide EasyBuild packages that can be used with the eb command. To install version 2019.7, use
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.
module load qiime2/2019.7
References
QIIME homepage
EasyBuild documentation
Getting started with Conda