How to use the CLI¶
XspecT comes with a built-in command line interface (CLI), which enables quick classifications without the need to use the web interface. The command line interface can also be used to download and train models.
After installing XspecT, a list of available commands can be viewed by running:
xspect --help
Model downloads¶
A basic set of pre-trained models (Acinetobacter and Salonella) can be downloaded using the following command:
xspect download-models
For the moment, it is not possible to specify exactly which models should be downloaded.
Classification¶
To classify samples, the command
xspect classify-species GENUS PATH
can be used, when GENUS
refers to the NCBI genus name of your sample and PATH
refers to the path to your sample directory. This command will classify the species of your sample within the given genus.
The following options are available:
-m, --meta / --no-meta Metagenome classification.
-s, --step INTEGER Sparse sampling step size (e. g. only every 500th
kmer for step=500).
--help Show this message and exit.
To speed up the analysis, only every nth kmer can be considered (“sparse sampling”). For example, to only consider every 10th kmer, run:
xspect classify-species -s 10 Acinetobacter path
Metagenome Mode¶
To analyze a sample in metagenome mode, the -m
/--meta
(--no-meta
) option can be used:
xspect classify-species -m Acinetobacter path
Compared to normal XspecT species classification, this mode first identifies reads belonging to the given genus and continues classification only with the resulting reads, It is thus more suitable for metagenomic samples as the resulting runtime is decreased.
MLST Classification¶
Samples can also be classified based on Multi-locus sequence type schemas. To MLST-classify a sample, run:
xspect classify-mlst -p path
Model Training¶
Models can be trained based on data from NCBI, which is automatically downloaded and processed by XspecT.
To train a model, run the following command:
xspect train-species your-ncbi-genus
you-ncbi-genus
can be a genus name from NCBI or an NCBI taxonomy ID.
To train models for MLST classifications, run:
xspect train-mlst