About
LISA is a statistical test for the influence of Transcription Factors on a set of genes. We leverage integrative modeling of public chromatin accessiblity and factor binding to make predictions that go beyond simple co-expression analysis. The minimum you need to run LISA is a list of genes-of-interest, but you can also supply your own epigenetic background. For more information, see Qin et al., 2020. This implementation extends the original, running faster, reducing dependencies, and adding useful CLI functions for pipeline integration.
Documentation
Please see Lisa's github repo for source code and tutorials.
Installation
Requirements
- Mac or Linux OS
- Python 3.6+
- 15 GB of available storage space
Installation
LISA will install data into the virutal environment's "site_packages" directory, so ensure the env's location can store ~10GB.
PyPI
It is recommended to install lisa to a virtual environment:
$ python3 -m venv .venvs/lisa_env
$ source .venvs/lisa_env/bin/activate
Install LISA to this virtual env using this command:
(lisa_env) $ pip install lisa2
Conda
First, create a virtual environment:
(base) $ conda create --name lisa_env
(base) $ conda activate lisa_env
Then install from Conda:
(lisa_env) $ conda install -c liulab-dfci lisa2
Dependencies
- numpy
- scipy
- h5py
- pyBigWig
- scikit-learn
1 maintainer
Metadata
1 maintainer
Release files for lisa2 2.2.5
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| File | Size | Uploaded | Provenance | |
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| lisa2-2.2.5.tar.gz | 6.6 MB | Without provenance | Details |
Release files / lisa2-2.2.5.tar.gz
| Download URL | lisa2-2.2.5.tar.gz |
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