The application of 2nd and 3rd generation High Throughput Sequencing (HTS) technologies has deeply reshaped experimental method to investigate microbial communities and obtain a taxonomic and functional profile of the invetigated community. Shotgun Metagenomics allow to quickly obtain a representation of microorganisms genomes characterizing a particular environment. In order to obtain a fast e reliable taxonomic classification of microorganisms genomes we present kMetaShot, an alignment-free taxonomic classifier based on k-mer/minimizer counting.
kMetaShot is available through conda. To install it type the following line:
conda create --name kmetashot kmetashot -c conda-forge -c gdefazio
To activate the environment:
conda activate kmetashot
kMetaShot requires a reference file available at this link. It requires about 22Gb of storage.
To download it you can simply use wget:
wget http://srv00.recas.ba.infn.it/webshare/brunofosso/kMetaShot_reference.h5
Before to use kMetaShot you may test the installation typing the following line:
kMetaShot_test.py -r /path/to/kMetaShot_reference.h5
kMetaShot_classifier_NV.py
-b bins/
-r kMetaShot_reference/kMetaShot_bacteria_archaea.h5',
-p 10
-o output_dir
-a 0.1
Arguments:
-h, --help show this help message and exit
-b , --bins_dir (char)
Path to a directory containing bins fasta files or
path to a multi-fasta file where each header corresponds
to a bin/MAG
-r , --reference (char)
Path to HDF5 kMetaShot reference
-p , --processes (int)
Number of child processes for a Multiprocess parallelism.
Warning: high parallelism <==> high RAM usage
-o , --out_dir (char)
Output directory
-a , --ass2ref (float)
Classification filtering based on ass2ref parameter ranging
between 0 and 1. Default 0.
kmetashot is also available as Docker container:
docker run -it ibiomcnr/kmetashot kMetaShot_classifier_NV.py --help