# Template

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

# groupings

Creates a sample grouping file for variant calling

usage
harpy template groupings INPUTS > output

example | generate a grouping file from folder of fastq/bam files
harpy template groupings data/ > samples.groups

# arguments

argument	description
`INPUTS`	required Files or directories containing input FASTQ/BAM files

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:

popgroups.txt
sample1 pop1
sample2 pop1
sample3 pop2
sample4 pop1
sample5 pop3

# hpc-*

Create template configurations for HPC cluster job submission systems (e.g. SLURM, HTConder) that can be provided to the --hpc option for workflows. You will likely also need to install the appropriate snakemake plugin(s) to use this feature. For example, to use the SLURM plugin, you will need to install snakemake-executor-plugin-slurm and likely snakemake-storage-plugin-fs (via pip, conda, etc.).

usage
harpy template hpc-system > out.yaml

example | create SLURM submission template
harpy template hpc-slurm > slurm.yaml

# impute

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. 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.

usage
harpy template impute > output

example | create imputation parameter template
harpy template impute > params.stitch

resulting params.stitch file
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