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countland

tools in python and R for analyzing biological count data, especially from single cell RNAseq

https://github.com/shchurch/countland

Science Score: 33.0%

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

  • ○
    CITATION.cff file
  • ○
    codemeta.json file
  • ○
    .zenodo.json file
  • ✓
    DOI references
    Found 3 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: biorxiv.org
  • ✓
    Committers with academic emails
    1 of 6 committers (16.7%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (11.5%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

tools in python and R for analyzing biological count data, especially from single cell RNAseq

Basic Info
  • Host: GitHub
  • Owner: shchurch
  • License: mit
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 114 MB
Statistics
  • Stars: 22
  • Watchers: 2
  • Forks: 5
  • Open Issues: 7
  • Releases: 0
Created over 4 years ago · Last pushed over 2 years ago
Metadata Files
Readme License

README.md

countland

Tools for analyzing biological count data, especially from single cell RNA-seq.

Please see our manuscript for more details:

Church et al. 2022. Normalizing need not be the norm: count-based math for analyzing single-cell data. bioRxiv https://doi.org/10.1101/2022.06.01.494334

countland is implemented in both R and python. The code for each is included in this repository.

python

Installation for python

countland is available with pip: https://pypi.org/project/countland/

To prepare a conda environment and install countland (before first use):

conda create -n countland -c conda-forge
conda activate countland
pip install countland

To activate the conda environment (before each use):

conda activate countland

The develompent version from in this repository can be installed using 

pip install git+https://github.com/shchurch/countland.git#subdirectory=countland-py

Running the tutorial in python

The easiest way to run the tutorial is as a Google Colab notebook. Just open the following link and follow the instructions:

https://colab.research.google.com/github/shchurch/countland/blob/main/tutorialsandvignettes/pythontutorialsandvignettes/vignettetutorial.ipynb

Alternatively, the python tutorial can be run locally in a jupyter notebook.

R

Installation for R

countland is available from CRAN: https://CRAN.R-project.org/package=countland

From an R prompt, run the following: 

install.packages("countland")

Teh development version from this repository can be installed using 

library(devtools)
install_github("shchurch/countland", subdir="countland-R")

Running the tutorial in R

The R tutorial can be run locally as an Rmarkdown file, e.g. knit in RStudio.

Development

See development.md for details.

Owner

  • Login: shchurch
  • Kind: user

GitHub Events

Total
  • Watch event: 1
Last Year
  • Watch event: 1

Committers

Last synced: over 3 years ago

All Time
  • Total Commits: 101
  • Total Committers: 6
  • Avg Commits per committer: 16.833
  • Development Distribution Score (DDS): 0.683
Top Committers
Name Email Commits
shchurch s****h@S****l 32
Casey Dunn c****n@y****u 29
shchurch s****h@s****n 19
shchurch 4****h@u****m 17
shchurch s****h@v****l 3
shchurch s****h@v****l 1
Committer Domains (Top 20 + Academic)
vpn172022121028.its.yale.internal: 1 vpn17225142246.its.yale.internal: 1 samuels-mbp-2.lan: 1 yale.edu: 1

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 17
  • Total pull requests: 2
  • Average time to close issues: about 2 months
  • Average time to close pull requests: 6 days
  • Total issue authors: 4
  • Total pull request authors: 2
  • Average comments per issue: 1.53
  • Average comments per pull request: 1.5
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • caseywdunn (8)
  • shchurch (7)
  • Gesmira (1)
  • krlmlr (1)
Pull Request Authors
  • olivroy (2)
  • krlmlr (1)
Top Labels
Issue Labels
enhancement (2) bug (1)
Pull Request Labels

Packages

  • Total packages: 2
  • Total downloads:
    • cran 231 last-month
    • pypi 5 last-month
  • Total dependent packages: 0
    (may contain duplicates)
  • Total dependent repositories: 0
    (may contain duplicates)
  • Total versions: 5
  • Total maintainers: 2
pypi.org: countland

tools for scRNA-seq analysis

  • Versions: 3
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 5 Last month
Rankings
Dependent packages count: 6.6%
Stargazers count: 14.2%
Average: 17.2%
Forks count: 17.3%
Dependent repos count: 30.6%
Maintainers (1)
shchurch
Last synced: 11 months ago
cran.r-project.org: countland

Analysis of Biological Count Data, Especially from Single-Cell RNA-Seq

  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 231 Last month
Rankings
Dependent packages count: 29.8%
Dependent repos count: 35.5%
Average: 46.9%
Downloads: 75.4%
Maintainers (1)
samuelhchurch@gmail.com
Last synced: 11 months ago

Dependencies

countland-R/DESCRIPTION cran
  • Matrix * imports
  • ggplot2 * imports
  • methods * imports
  • rlang * imports
  • RSpectra * suggests
  • Seurat * suggests
  • gridExtra * suggests
  • igraph * suggests
  • matrixTests * suggests
  • rdist * suggests
  • stats * suggests
  • testthat >= 3.0.0 suggests
  • tidyverse * suggests
  • viridis * suggests
countland-py/pyproject.toml pypi
countland-py/setup.py pypi