# Cell-free DNA analysis toolkit
[](https://travis-ci.org/kylessmith/cfdna) [](https://badge.fury.io/py/cfdna)
This is a Python package for easy and efficient cell-free
DNA analysis.
All citations should reference to [original paper][paper].
## Install
If you dont already have numpy and scipy installed, it is best to download
`Anaconda`, a python distribution that has them included.
```
https://continuum.io/downloads
```
Create environment and pip install:
```
conda create -n cfdna python=3.11.3
conda activate cfdna
pip install cfdna==2.0.5
```
Dependencies can be installed by:
```
pip install -r requirements.txt
```
PyPI install, presuming you have all its requirements installed:
```
pip install cfdna
```
## Usage
```python
import cfdna as cf
import numpy as np
# Create data
cfdata = cf.cfDNA()
frags = cf.io.readBAM("test.bam")
# Call CNVs
cf.proc.call_cnv_pipline(cfdata, frags)
# Plot CNVs
cf.pl.plot_cnv(cfdata, "test.bam")
```
Run from the commadline:
```
python -m cfdna callCNVs --bam test.bam --segs --genome hg19 --bin_size 100000
```
This will output a .png plot and seg file.
[paper]: https://www.cell.com/cancer-cell/pdfExtended/S1535-6108(21)00501-8
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"description": "# Cell-free DNA analysis toolkit\n\n[](https://travis-ci.org/kylessmith/cfdna) [](https://badge.fury.io/py/cfdna)\n\nThis is a Python package for easy and efficient cell-free\nDNA analysis.\n\nAll citations should reference to [original paper][paper].\n\n\n## Install\n\nIf you dont already have numpy and scipy installed, it is best to download\n`Anaconda`, a python distribution that has them included. \n```\n https://continuum.io/downloads\n```\n\nCreate environment and pip install:\n```\n conda create -n cfdna python=3.11.3\n\tconda activate cfdna\n\tpip install cfdna==2.0.5\n```\n\nDependencies can be installed by:\n\n```\n pip install -r requirements.txt\n```\n\nPyPI install, presuming you have all its requirements installed:\n```\n pip install cfdna\n```\n\n## Usage\n\n```python\nimport cfdna as cf\nimport numpy as np\n\n# Create data\ncfdata = cf.cfDNA()\nfrags = cf.io.readBAM(\"test.bam\")\n\n# Call CNVs\ncf.proc.call_cnv_pipline(cfdata, frags)\n\n# Plot CNVs\ncf.pl.plot_cnv(cfdata, \"test.bam\")\n```\n\nRun from the commadline:\n\n```\n python -m cfdna callCNVs --bam test.bam --segs --genome hg19 --bin_size 100000\n```\n\nThis will output a .png plot and seg file.\n\n[paper]: https://www.cell.com/cancer-cell/pdfExtended/S1535-6108(21)00501-8",
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