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Running the analysis
It might be useful to have a look at what will happen if you start the ARMOR workflow with your current setup. To do this, run snakemake --use-conda -npr
or snakemake -npr
if you do not want to use conda. The -n
parameter causes a dryrun, i.e. no execution and just displaying what will be done. The -p
parameter prints the shell commands that will be executed by the pipeline; good for checking if file paths are correct. The -r
parameter prints the reason why each rule will be executed (e.g. missing output file, new timestamp,...).
If all the paths and individual configurations are defined in the config.yaml
file (see configuration) and conda
is available (see managing software), the workflow can be run from the command line with
snakemake --use-conda
Snakemake will create a conda
environment from the envs/environment.yaml
file and it will activate the environment before executing all rules with the conda
directive. If you are an experienced conda
user, you can specify a different environment for each rule within the Snakefile
, and the correct environment will be activated.
If you want to use multiple cores, just do
snakemake --use-conda --cores 12
If you want to run a specific rule, just do
snakemake --use-conda <ruleName>
First make sure the paths to all your input files are specified correctly in the config.yaml
(see here). Relative paths will be interpreted relative to the Snakefile
directory! To run the workflow outside of the folder containing the Snakefile
(and all the scripts), specify the Snakefile
path, and the path to the folder containing this file
snakemake --use-conda -s <path-to-Snakefile> -d <workdir>
Where workdir
is the directory of the Snakefile
.
If you want to use a config.yaml
file that is not located in the Snakefile
directory, you can specify it with the --configfile
parameter. Run the workflow from the Snakefile
directory with
snakemake --use-conda --configfile <path-to-config.yaml>
Or see above for how to run the workflow from an arbitrary directory.
After setting up your conda
environment and system R installation (read first here), activate the environment and from within the environment run the pipeline with snakemake
. For multiple cores use snakemake --cores 12
.
In case you have all the necessary software in your path (see here) and you don't want to use conda
, simply run the workflow without the --use-conda
parameter:
snakemake
.
Summary: If you do not want to use conda to manage your software (i.e. run-mode 2 and 3 of Managing software, simply omit the --use-conda
parameter from the example commands.
If invoked as described above, snakemake
will execute a rule if the output is out-of-date with respect to the input, as determined by the time stamps of the corresponding files. In order to force re-execution in cases where the parameters (defined in the config.yaml
file) have changed, call snakemake
as:
snakemake --use-conda -R `snakemake --list-params-changes`
--list-params-changes
will list the files that use any of the updated parameters, and -R
will force their regeneration. See here for more details.
Use
snakemake -D > summary.txt
To generate a detailed summary of your run after it's finished, without re-running the workflow. As explained in the snakemake manual: Prints a summary of all files created by the workflow. The has the following columns: filename, modification time, rule version, input file(s), shell command, status, plan.
or use
snakemake --report report.html
To generate a nice visual report of running times and statistics of your run.