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# Sphinx build info version 1
# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
config: d8158e6d80a4e413539252e5d79255e7
tags: 645f666f9bcd5a90fca523b33c5a78b7
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14 changes: 14 additions & 0 deletions _sources/develop.md.txt
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Contributing to SnapATAC2
=========================

## A brief guide to adding new features to SnapATAC2

The SnapATAC2 Github repository contains three libraries:

1. `snapatac2-core`: Core functions written in Rust.
2. `snapatac2-python`: High-level user-facing functions written in mostly Python.
3. `snapatac2-contrib`: Python package containing additional features from external contributors.

Unless the new feature is essential and highly relevant to functions in the core library, it is recommended to add it to the `snapatac2-contrib` library.
Otherwise, add the feature to the `snapatac2-python` library under the `snapatac2.experimental` module.
We will move function from `snapatac2.experimental` to `snapatac2` once they are sufficiently tested and stable.
30 changes: 30 additions & 0 deletions _sources/index.rst.txt
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SnapATAC2: A Python/Rust package for single-cell epigenomics analysis
=====================================================================

SnapATAC2 is a flexible, versatile, and scalable single-cell omics analysis framework, featuring:

- Scale to more than 10 million cells.
- Blazingly fast preprocessing tools for BAM to fragment files conversion and count matrix generation.
- Matrix-free spectral embedding algorithm that is applicable to a wide range of single-cell omics data, including single-cell ATAC-seq, single-cell RNA-seq, single-cell Hi-C, and single-cell methylation.
- Efficient and scalable co-embedding algorithm for single-cell multi-omics data integration.
- End-to-end analysis pipeline for single-cell ATAC-seq data, including preprocessing, dimension reduction, clustering, data integration, peak calling, differential analysis, motif analysis, regulatory network analysis.
- Seamless integration with other single-cell analysis packages such as Scanpy.
- Implementation of fully backed AnnData.

How to cite
-----------

The SnapATAC2 manuscript has not been published yet. The key algorithms used in
SnapATAC2 have been described in the following papers:

- Zhang, K. et al. A single-cell atlas of chromatin accessibility in the human genome. Cell 184, 5985-6001.e19 (2021).
- Fang, R. et al. Comprehensive analysis of single cell ATAC-seq data with SnapATAC. Nat Commun 12, 1337 (2021).

.. toctree::
:maxdepth: 3
:hidden:

install
tutorials/index
reference/index
Development<develop>
79 changes: 79 additions & 0 deletions _sources/install.md.txt
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Installation
============

Stable version
--------------

Stable versions of SnapATAC2 are published on PyPI.
Precompiled binaries are available for x86_64 Linux systems and macOS.
So installing it is as simple as running:

```
pip install snapatac2
```

If there are no precompiled binaries published for your system, you will have to
build the package from source.
Building the SnapATAC2 library requires `cmake >= 3.5.1` and
the [Rust](https://www.rust-lang.org/tools/install) compiler. You need to install
them first if they are not available on your system.
You can find the instructions for installing cmake [here](https://cmake.org/install/).
The Rust compiler can be installed using:

```
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
rustup default nightly
```

Once you have cmake and the Rust compiler properly installed,
running `pip install snapatac2` will build SnapATAC2 from the source package and
install it just as it would if there was a prebuilt binary available.

Nightly build
-------------

The nightly build is the build from the latest source codes, which includes the
latest features, enhancements, and bug fixes that haven't been released.
The nightly build can be unstable and include some untested features.

You can download the wheel files of the latest Nightly build from this
[link](https://nightly.link/kaizhang/SnapATAC2/workflows/wheels/main/artifact.zip).

After downloading the file, unzip it and then select the appropriate wheel file
for your platform and use `pip install` to install it.

Build from the latest source code
---------------------------------

Building the SnapATAC2 library requires `cmake >= 3.5.1` and
the [Rust](https://www.rust-lang.org/tools/install) compiler. You need to install
them first if they are not available on your system.
You can find the instructions for installing cmake [here](https://cmake.org/install/).
The Rust compiler can be installed using:

```
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
rustup default nightly
```

Once you have cmake and the Rust compiler properly installed,
clone the source code repository and go to the `snapatac2-python` directory,
use `pip install .` to install the package.

```
git clone https://github.com/kaizhang/SnapATAC2.git
cd SnapATAC2/snapatac2-python
pip install .
```

Optional dependencies
---------------------

Here is a list of optional dependencies used by SnapATAC2:

- `macs2`: Peak calling.
- `harmonypy`: Batch correction using the Harmony.
- `xgboost`: Regulatory network analysis.

Optional dependencies are not installed by SnapATAC2. Please install them
manually if necessary.
6 changes: 6 additions & 0 deletions _sources/reference/_autosummary/snapatac2.AnnData.X.rst.txt
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snapatac2.AnnData.X
===================

.. currentmodule:: snapatac2

.. autoattribute:: AnnData.X
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snapatac2.AnnData.backend
=========================

.. currentmodule:: snapatac2

.. autoattribute:: AnnData.backend
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snapatac2.AnnData.chunked\_X
============================

.. currentmodule:: snapatac2

.. automethod:: AnnData.chunked_X
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snapatac2.AnnData.close
=======================

.. currentmodule:: snapatac2

.. automethod:: AnnData.close
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snapatac2.AnnData.copy
======================

.. currentmodule:: snapatac2

.. automethod:: AnnData.copy
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snapatac2.AnnData.filename
==========================

.. currentmodule:: snapatac2

.. autoattribute:: AnnData.filename
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snapatac2.AnnData.is\_closed
============================

.. currentmodule:: snapatac2

.. automethod:: AnnData.is_closed
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snapatac2.AnnData.isbacked
==========================

.. currentmodule:: snapatac2

.. autoattribute:: AnnData.isbacked
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snapatac2.AnnData.layers
========================

.. currentmodule:: snapatac2

.. autoattribute:: AnnData.layers
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snapatac2.AnnData.n\_obs
========================

.. currentmodule:: snapatac2

.. autoattribute:: AnnData.n_obs
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snapatac2.AnnData.n\_vars
=========================

.. currentmodule:: snapatac2

.. autoattribute:: AnnData.n_vars
6 changes: 6 additions & 0 deletions _sources/reference/_autosummary/snapatac2.AnnData.obs.rst.txt
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snapatac2.AnnData.obs
=====================

.. currentmodule:: snapatac2

.. autoattribute:: AnnData.obs
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snapatac2.AnnData.obs\_ix
=========================

.. currentmodule:: snapatac2

.. automethod:: AnnData.obs_ix
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snapatac2.AnnData.obs\_names
============================

.. currentmodule:: snapatac2

.. autoattribute:: AnnData.obs_names
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snapatac2.AnnData.obsm
======================

.. currentmodule:: snapatac2

.. autoattribute:: AnnData.obsm
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snapatac2.AnnData.obsp
======================

.. currentmodule:: snapatac2

.. autoattribute:: AnnData.obsp
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snapatac2.AnnData.open
======================

.. currentmodule:: snapatac2

.. automethod:: AnnData.open
53 changes: 53 additions & 0 deletions _sources/reference/_autosummary/snapatac2.AnnData.rst.txt
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snapatac2.AnnData
=================

.. currentmodule:: snapatac2

.. autoclass:: AnnData



.. rubric:: Attributes

.. autosummary::
:toctree: .

~snapatac2.AnnData.X
~snapatac2.AnnData.backend
~snapatac2.AnnData.filename
~snapatac2.AnnData.isbacked
~snapatac2.AnnData.layers
~snapatac2.AnnData.n_obs
~snapatac2.AnnData.n_vars
~snapatac2.AnnData.obs
~snapatac2.AnnData.obs_names
~snapatac2.AnnData.obsm
~snapatac2.AnnData.obsp
~snapatac2.AnnData.shape
~snapatac2.AnnData.uns
~snapatac2.AnnData.var
~snapatac2.AnnData.var_names
~snapatac2.AnnData.varm
~snapatac2.AnnData.varp





.. rubric:: Methods

.. autosummary::
:toctree: .

~snapatac2.AnnData.chunked_X
~snapatac2.AnnData.close
~snapatac2.AnnData.copy
~snapatac2.AnnData.is_closed
~snapatac2.AnnData.obs_ix
~snapatac2.AnnData.open
~snapatac2.AnnData.subset
~snapatac2.AnnData.to_memory
~snapatac2.AnnData.var_ix
~snapatac2.AnnData.write


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snapatac2.AnnData.shape
=======================

.. currentmodule:: snapatac2

.. autoattribute:: AnnData.shape
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snapatac2.AnnData.subset
========================

.. currentmodule:: snapatac2

.. automethod:: AnnData.subset
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snapatac2.AnnData.to\_memory
============================

.. currentmodule:: snapatac2

.. automethod:: AnnData.to_memory
6 changes: 6 additions & 0 deletions _sources/reference/_autosummary/snapatac2.AnnData.uns.rst.txt
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snapatac2.AnnData.uns
=====================

.. currentmodule:: snapatac2

.. autoattribute:: AnnData.uns
6 changes: 6 additions & 0 deletions _sources/reference/_autosummary/snapatac2.AnnData.var.rst.txt
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snapatac2.AnnData.var
=====================

.. currentmodule:: snapatac2

.. autoattribute:: AnnData.var
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snapatac2.AnnData.var\_ix
=========================

.. currentmodule:: snapatac2

.. automethod:: AnnData.var_ix
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snapatac2.AnnData.var\_names
============================

.. currentmodule:: snapatac2

.. autoattribute:: AnnData.var_names
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snapatac2.AnnData.varm
======================

.. currentmodule:: snapatac2

.. autoattribute:: AnnData.varm
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snapatac2.AnnData.varp
======================

.. currentmodule:: snapatac2

.. autoattribute:: AnnData.varp
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