Metadata-Version: 2.4
Name: run-dipc
Version: 1.9.7
Summary: Diploid chromatin conformation capture analysis
Author: Longzhi Tan
License: MIT License
        
        Copyright (c) 2018 Longzhi Tan and contributors
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
        
Project-URL: Homepage, https://github.com/tanlongzhi/dip-c
Project-URL: Repository, https://github.com/tanlongzhi/dip-c
Keywords: bioinformatics,chromatin,Hi-C,3D genome,single-cell
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.22
Requires-Dist: scipy>=1.7
Requires-Dist: rmsd>=1.5
Requires-Dist: mmcif-pdbx>=2.0
Requires-Dist: pysam>=0.20
Provides-Extra: dev
Requires-Dist: pytest>=7.0; extra == "dev"
Requires-Dist: pytest-cov; extra == "dev"
Provides-Extra: docs
Requires-Dist: mkdocs-material; extra == "docs"
Requires-Dist: mkdocs<2,>=1.5; extra == "docs"
Dynamic: license-file

# Dip-C

**Dip**loid **C**hromatin Conformation Capture — reconstruct 3D diploid genomes from single cells.

## Installation

| Method | When to use | Install time |
|--------|-------------|--------------|
| conda + pip (recommended) | Works everywhere; best for HPC clusters and older Linux | ~1 minute |
| pip only | Modern systems: macOS, Ubuntu 20.04+, RHEL 8+ | ~15 seconds |
| pip only (source build) | Older Linux (e.g. CentOS/RHEL 7, Stanford Sherlock); not recommended — use conda + pip instead | 15–30 minutes |

### Recommended installation (conda + pip)

The easiest way to ensure that the installation will work on your system, regardless of the age of its software, is to create a conda environment and pre-install the compiled dependencies, then install Dip-C with pip:

```bash
conda create -n dipc python=3.11
conda activate dipc
conda install -c conda-forge -c bioconda numpy scipy pysam
pip install run-dipc
```

> **Note:** If you see `Run 'conda init' before 'conda activate'` (common on
> HPC clusters), run this first:
>
> ```bash
> source $(conda info --base)/etc/profile.d/conda.sh
> ```

Verify the installation:

```bash
dip-c --help
```

### Alternative: pip-only install

On modern systems (macOS, Ubuntu 20.04+, RHEL 8+), pip can install everything directly. This is worth trying, but if it fails for any reason we suggest using the above conda + pip installation method:

```bash
pip install run-dipc
```

> **Why does pip fail on older Linux? (optional reading):** If pip failed, use the conda + pip
> method above. Older systems like CentOS/RHEL 7 have an old C library
> (glibc < 2.28), so prebuilt packages for NumPy, SciPy, and pysam are not
> available. Pip falls back to compiling them from source, which takes
> **15–30 minutes** and requires a C++17-capable compiler. If that build also
> fails with `C++ Compiler does not support -std=c++17`, the system's C++
> compiler is too old. You can install a newer one with:
>
> ```bash
> conda install -c conda-forge gcc_linux-64 gxx_linux-64
> ```
>
> But the simplest path is to skip all of this and use the recommended
> conda + pip installation above.

## Usage

```bash
dip-c <command> [options]
```

Run `dip-c` with no arguments to see all available commands.

## Documentation

Full documentation, workflows, and file format specifications are available on GitHub:

**https://github.com/tanlongzhi/dip-c**

## Citations

Please cite the original Dip-C paper:

> Tan, Longzhi\*; Xing, Dong\*; Chang, Chi-Han; Li, Heng; Xie, X. Sunney "Three-dimensional genome structures of single diploid human cells," *Science* **361**, 924-928 (2018). [DOI:10.1126/science.aat5641](https://doi.org/10.1126/science.aat5641)

## License

MIT
