Data

Tools

Indexes

Applications

Experiments

Open Source Science

py_presto

R package "immunogenomics/presto" adapted for python users

https://github.com/raginimedhi/py_presto

Science Score: 44.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (5.2%) to scientific vocabulary
Last synced: 9 months ago · JSON representation ·

Repository

R package "immunogenomics/presto" adapted for python users

Basic Info
  • Host: GitHub
  • Owner: RaginiMedhi
  • Language: Python
  • Default Branch: main
  • Size: 88.9 KB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created almost 2 years ago · Last pushed over 1 year ago
Metadata Files
Readme Citation

README.md

The R package "immunogenomics/presto" (refer to: https://github.com/immunogenomics/presto) provides Wilcoxon rank sum test and auROC analyses for single cell RNA-seq data which are inherently sparse.

Here, the functions have been adapted to be compatible with python and to ensure analyses of single cell matrices in python.

Instructions for implementation are provided as "pythonprestotutorial.ipynb" in the code folder.

Disclaimer: This is a personal project and is not associated with the official R package/authors of presto. Please feel free to use or adapt as per your use case. Citation functionality is provided for referring to this work when necessary.

Owner

  • Name: Ragini Medhi
  • Login: RaginiMedhi
  • Kind: user
  • Company: CRH

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Medhi"
  given-names: "Ragini"
  orcid: "https://orcid.org/0000-0002-2780-0708"
title: "Python implementation for the R package: immunogenomics/presto"
version: 1.0.0
date-released: 2024-07-29
url: "https://github.com/RaginiMedhi/py_presto"

GitHub Events

Total
Last Year

Dependencies

Dockerfile docker
  • python 3.12.2 build
requirements.txt pypi
  • Pygments ==2.18.0
  • anndata ==0.10.8
  • array_api_compat ==1.8
  • asttokens ==2.4.1
  • comm ==0.2.2
  • contourpy ==1.2.1
  • cycler ==0.12.1
  • debugpy ==1.8.2
  • decorator ==5.1.1
  • executing ==2.0.1
  • fonttools ==4.53.1
  • h5py ==3.11.0
  • iniconfig ==2.0.0
  • ipykernel ==6.29.5
  • ipython ==8.26.0
  • jedi ==0.19.1
  • joblib ==1.4.2
  • jupyter_client ==8.6.2
  • jupyter_core ==5.7.2
  • kiwisolver ==1.4.5
  • legacy-api-wrap ==1.4
  • llvmlite ==0.43.0
  • matplotlib ==3.9.1
  • matplotlib-inline ==0.1.7
  • natsort ==8.4.0
  • nest-asyncio ==1.6.0
  • networkx ==3.3
  • numba ==0.60.0
  • numpy ==1.26.4
  • packaging ==24.1
  • pandas ==2.2.2
  • parso ==0.8.4
  • patsy ==0.5.6
  • pexpect ==4.9.0
  • pillow ==10.4.0
  • platformdirs ==4.2.2
  • pluggy ==1.5.0
  • prompt_toolkit ==3.0.47
  • psutil ==6.0.0
  • ptyprocess ==0.7.0
  • pure_eval ==0.2.3
  • pynndescent ==0.5.13
  • pyparsing ==3.1.2
  • pytest ==8.3.2
  • python-dateutil ==2.9.0.post0
  • pytz ==2024.1
  • pyzmq ==26.0.3
  • scanpy ==1.10.2
  • scikit-learn ==1.5.1
  • scipy ==1.14.0
  • seaborn ==0.13.2
  • session_info ==1.0.0
  • setuptools ==69.1.1
  • six ==1.16.0
  • stack-data ==0.6.3
  • statsmodels ==0.14.2
  • stdlib-list ==0.10.0
  • threadpoolctl ==3.5.0
  • tornado ==6.4.1
  • tqdm ==4.66.4
  • traitlets ==5.14.3
  • tzdata ==2024.1
  • umap-learn ==0.5.6
  • wcwidth ==0.2.13
  • wheel ==0.43.0