Package for cell type genomics
Project description
CellTypeGenomics
Overview
CellTypeGenomics is an open-source Python package designed to analyze the cell-type origins of genes using Human Protein Atlas (HPA) data. It helps to identify genes that are potentially over-represented or under-represented in specific cell types, providing insights that are crucial for understanding various biological processes and diseases.
The recent update made it possible to replace our numerical Human Protein Atlas (HPA) marker genes (proteinatlas.tsv) with qualitative marker genes from the human Ensemble Cell Atlas (hECA) or the Human Protein Atlas (HPA). In addition, there is an option to return tissue origins of genes using Human Protein Atlas (HPA) data.
Key Functionality
- Gene Analysis: Analyzes a list of gene Ensembl IDs and returns a sorted pandas DataFrame, highlighting genes that are potentially over- or under-represented in certain cell types.
- Data Source: Leverages the comprehensive gene expression data available from the Human Protein Atlas (HPA) and the human Ensemble Cell Atlas (hECA).
Installation
To install CellTypeGenomics, run the following command in your terminal:
pip install celltypegenomics
Usage
Here's how to use the CellTypeGenomics package to analyze your gene list with numerical Human Protein Atlas (HPA) marker genes:
from celltypegenomics import celltypefishertest
# Specify an optional alpha for significance (default: 0.05)
result = celltypefishertest(list_of_ensembl_ids, alpha=0.05)
print(result)
Replace list_of_ensembl_ids
with your list of gene Ensembl IDs.
Use CellTypeGenomics package to analyze your gene list with qualitative marker genes from the human Ensemble Cell Atlas (hECA):
result = celltypefishertest(list_of_ensembl_ids, heca=True)
print(result)
Use CellTypeGenomics package to analyze your gene list with qualitative marker genes from the Human Protein Atlas (HPA):
result = celltypefishertest(list_of_ensembl_ids, hpa_marker_genes=True)
print(result)
Use CellTypeGenomics package to analyze your gene list with tissue origins of genes using Human Protein Atlas (HPA):
result = celltypefishertest(list_of_ensembl_ids, tissue=True)
print(result)
Support
For more information, updates, or to contribute to the project, please visit our GitHub Repository.
License
CellTypeGenomics is released under the MIT license. See the LICENSE file for more details.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file celltypegenomics-0.0.5.tar.gz
.
File metadata
- Download URL: celltypegenomics-0.0.5.tar.gz
- Upload date:
- Size: 572.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.0.0 CPython/3.12.3
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 1c2281b2f3a268ef0820fb9bdfeddad634b569fb1b282dd4a8738f31088ba31e |
|
MD5 | 7f1a8ac9b61c100d9d356a288534f86b |
|
BLAKE2b-256 | ec749d3a97d555ef3b509bc14c928c1d57e06a41c2a7dddae6953a359b495b59 |
File details
Details for the file celltypegenomics-0.0.5-py3-none-any.whl
.
File metadata
- Download URL: celltypegenomics-0.0.5-py3-none-any.whl
- Upload date:
- Size: 601.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.0.0 CPython/3.12.3
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | c3a44bcf1de85ee9b95b42a8161a19296aaf10594fc38a1671ffc9a89fc11a1f |
|
MD5 | 3b85f3a98c8f9ac71fd35b7ea437d0d8 |
|
BLAKE2b-256 | 26cae32cf406a18087ef6799b70e487f0c4328fe9d518e48274f78aa1d1366d6 |