This is a QIIME 2 plugin. For details on QIIME 2, see https://qiime2.org. For details on sourmash, see http://sourmash.readthedocs.io/.
q2-sourmash is a QIIME 2 plugin for sourmash, a tool computing and comparing MinHash signatures for nucleotide sequences fast and effieciently. You can find out more about sourmash by reading the paper (Brown and Irber, JOSS 2018) or checking out the sourmash documentation.
You need to have QIIME 2 version 2018.4 or later. Also, regardless of which way you install, you need to be in a QIIME 2 environment for this to work. Install QIIME 2 and activate the QIIME 2 virtual environment (e.g. source activate qiime2-2018.8), and then install sourmash by running:
conda install -c bioconda sourmash
You will also need to install q2-types-genomics (unless your environment already has it):
conda install -c conda-forge -c bioconda -c https://packages.qiime2.org/qiime2/2023.5/tested -c defaults \
q2-types-genomics
To install the plugin, run the following command:
pip install https://github.com/dib-lab/q2-sourmash/archive/master.zip
To check that the installation worked, type qiime on the command line. The sourmash plugin should show up in the list of available plugins.
Currently there are two main methods for use in the QIIME 2 sourmash plugin: compute to calcualte MinHash signatures from nucleotide sequences and compare to calculate a Jaccard distance between samples.
The compute calcuates the minhash signatures for a given set of nucleotide sequences. To run, one must simply supply a .qza archive (directory) containing sequence file ending with 'fastq.gz'.
First download a test set of fastq.gz files already in the form of a qza archive and the associated metadata. Here we are using data from the Moving Pictures tutorial:
wget -c -nc https://docs.qiime2.org/2018.4/data/tutorials/moving-pictures/demux.qza
wget -c -nc https://data.qiime2.org/2018.8/tutorials/moving-pictures/sample_metadata.tsv
To calculate sourmash signatures for all sequence files within the archive use the following:
qiime sourmash compute --i-sequence-file demux.qza --p-ksizes 21 --p-scaled 10000 --o-min-hash-signature sigs.qza
The following flags are required:
--i-sequence-file: the path to the qza directory--p-ksizes: the k-size of the hash (integer)--p-scaled: the scaled value (integer)--o-min-hash-signature: the output qza file name
The output archive, in this case sigs.qza, contains the signature files for each of the fastq.gz files that were input. They can be viewed using the qiime online viewer or by unzipping the qza file.
qiime tools export --input-path sigs.qza --output-path sigs
Signatures that have been calculated as above can then be compared using sourmash compare. This will calculate a pair-wise Jaccard distance between each of the samples included in the provided qza archive:
qiime sourmash compare --i-min-hash-signature sigs.qza --p-ksize 21 --o-compare-output compare.mat.qza
The output, compare.mat.qza, can then be investigated as above by unzipping the qza archive or can be pushed through subsequent analyses (e.g. generate a PCoA plot):
qiime diversity pcoa --i-distance-matrix compare.mat.qza --o-pcoa pcoa.compare.mat.qza
qiime emperor plot --i-pcoa pcoa.compare.mat.qza --o-visualization emperor.qzv --m-metadata-file sample_metadata.tsv