# Other Harpy modules

On this page you'll find Harpy functions that do other, ancillary things.

This will run dry-run Snakemake for a workflow with the --dry-run --debug-dag options and print output to try to identify why Snakemake might be stalling for a workflow. This is typically used during development or for troubleshooting edge-cases and you're likely/hopefully not going to need to use this feature.

Creating template/boilerplate files has been consolidated into harpy template. These commands will generate a specific file and write to stdout.

Creates a sample grouping file for variant calling

harpy template groupings INPUTS > output

harpy template groupings data/ > samples.groups

This optional file is useful if you want SNP variant calling to happen on a per-population level via harpy snp or on samples pooled-as-populations via harpy sv .

• takes the format of sample tab group
• all the samples will be assigned to group pop1 since file names don't always provide grouping information
  • so make sure to edit the second column to reflect your data correctly.
• the file will look like:

sample1 pop1
sample2 pop1
sample3 pop2
sample4 pop1
sample5 pop3

Create template configurations for HPC cluster job submission systems (e.g. SLURM, HTConder) that can be provided to the --hpc option for workflows.

harpy template hpc-system > out.yaml

harpy template hpc-slurm > slurm.yaml

Create a template parameter file for the impute module. The file is formatted correctly and serves as a starting point for using parameters that make sense for your study.

harpy template impute > output

harpy template impute > params.stitch

Typically, one runs STITCH multiple times, exploring how results vary with different model parameters. The solution Harpy uses for this is to have the user provide a tab-delimited dataframe file where the columns are the 6 STITCH model parameters and the rows are the values for those parameters. To make formatting easier, a template file is generated for you, just replace the values and add/remove rows as necessary. See the section for the impute module for details on these parameters. The template file will look like:

name model	usebx	bxlimit	k	s	ngen
k10_ng50 diploid	TRUE	50000	3	2	10
k1_ng30 diploid	TRUE	50000	3	1	5
high_ngen   diploid TRUE    50000   15  1   100

When calling a workflow (e.g. qc ), Harpy performs various file checks and validations, sets up the Snakemake command, output folder(s), etc. In the event you want to continue a failed or manually terminated workflow without overwriting the workflow files (e.g. config.harpy.yaml), you can use harpy resume . Using resume also skips all input/argument validations.

harpy resume [--conda] DIRECTORY

The DIRECTORY is the output directory of a previous harpy-invoked workflow, which must have the workflow/config.yaml file. For example, if you previously ran harpy align bwa -o align-bwa ..., then you would use harpy resume align-bwa, which would have the necessary workflow/config.yaml (and other necessary things) required to successfully continue the workflow. Using resume does not overwrite any preprocessing files in the target directory (whereas rerunning the workflow would), which means you can also manually modify the config.yaml file (advanced, not recommended unless you are confident with what you're doing).

resume also requires an existing and populated workdir/envs/ directory in the target directory, like the kind all main harpy workflows would create. If one is not present, you can use --conda to create one.

This convenience command lets you view important details within a Harpy workflow directory without having to fish around for the right files.

harpy view MODE DIRECTORY

harpy view config Align/bwa