Dip-C
Diploid Chromatin 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:
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:source $(conda info --base)/etc/profile.d/conda.sh
Verify the installation:
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:
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:conda install -c conda-forge gcc_linux-64 gxx_linux-64But the simplest path is to skip all of this and use the recommended conda + pip installation above.
Upgrading
If you already have Dip-C installed and want to update to the latest version:
pip install --upgrade run-dipc
Usage
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
License
MIT
Metadata
Release files for run-dipc 1.9.10
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| run_dipc-1.9.10.tar.gz | 39.0 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| run_dipc-1.9.10-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 51.2 MB
Release files / run_dipc-1.9.10.tar.gz
| Download URL | run_dipc-1.9.10.tar.gz |
|---|---|
| Size | 39.0 MB |
| Tags | Source |
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| Tags | Python 3 |
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