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Merge pull request #202 from jeromekelleher/move-cli-reference
Move cli reference
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docs/_toc.yml

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root: intro
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chapters:
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- file: installation
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- file: vcf2zarr
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- file: vcfpartition
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- file: cli
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- file: vcf2zarr/overview
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sections:
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- file: vcf2zarr/tutorial
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- file: vcf2zarr/cli_ref
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- file: vcfpartition/overview
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sections:
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- file: vcfpartition/cli_ref

docs/cli.md renamed to docs/vcf2zarr/cli_ref.md

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% Based on: https://github.com/skypilot-org/skypilot/pull/2834
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```{eval-rst}
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.. _cmd-vcf2zarr:
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.. click:: bio2zarr.cli:vcf2zarr_main
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:prog: vcf2zarr
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## Explode
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```{eval-rst}
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.. _cmd-vcf2zarr-explode:
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.. click:: bio2zarr.cli:explode
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:prog: vcf2zarr explode
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:nested: full

docs/vcf2zarr.md renamed to docs/vcf2zarr/overview.md

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---
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jupytext:
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formats: md:myst
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text_representation:
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extension: .md
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format_name: myst
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kernelspec:
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display_name: Bash
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language: bash
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name: bash
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---
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# vcf2zarr
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## Overview
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Convert a VCF to zarr format:
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```
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arriving at settings with the desired balance of compression and query
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performance.
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## Tutorial
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This is a step-by-step tutorial showing you how to convert your
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VCF data into Zarr format. There's three different ways to
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convert your data, basically providing different levels of
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convenience and flexibility corresponding to what you might
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need for small, intermediate and large datasets.
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### Small
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<!-- ```{code-cell} bash -->
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<!-- vcf2zarr convert ../tests/data/vcf/sample.vcf.gz sample.zarr -vf -->
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<!-- ``` -->
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<div id="vcf2zarr_convert"></div>
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<script>
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AsciinemaPlayer.create('_static/vcf2zarr_convert.cast',
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document.getElementById('vcf2zarr_convert'), {
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cols:80,
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rows:12
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});
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</script>
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### Intermediate
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### Large

docs/vcf2zarr/tutorial.md

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---
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jupytext:
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formats: md:myst
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text_representation:
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extension: .md
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format_name: myst
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kernelspec:
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display_name: Bash
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language: bash
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name: bash
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---
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# Tutorial
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This is a step-by-step tutorial showing you how to convert your
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VCF data into Zarr format. There's three different ways to
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convert your data, basically providing different levels of
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convenience and flexibility corresponding to what you might
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need for small, intermediate and large datasets.
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## Small
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<!-- ```{code-cell} bash -->
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<!-- vcf2zarr convert ../tests/data/vcf/sample.vcf.gz sample.zarr -vf -->
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<!-- ``` -->
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<div id="vcf2zarr_convert"></div>
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<script>
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AsciinemaPlayer.create('_static/vcf2zarr_convert.cast',
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document.getElementById('vcf2zarr_convert'), {
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cols:80,
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rows:12
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});
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</script>
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## Intermediate
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## Large
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docs/vcfpartition/cli_ref.md

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# CLI Reference
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```{eval-rst}
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.. click:: bio2zarr.cli:vcfpartition
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:prog: vcfpartition
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:nested: full
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```

docs/vcfpartition.md renamed to docs/vcfpartition/overview.md

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**TODO give a nice example here using xargs**
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**WARNING that this does not take into account that indels may overlap
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partitions and you may count variants twice or more if they do**
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**WARNING that this does not take into account that indels may overlap**

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