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scDDboost

R package for an empirical Bayesian statistical method to detect changes in the distribution of single-cell RNA-Seq data

https://github.com/wiscstatman/scddboost

Science Score: 33.0%

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

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    CITATION.cff file
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    codemeta.json file
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    .zenodo.json file
  • ✓
    DOI references
    Found 3 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: biorxiv.org
  • ✓
    Committers with academic emails
    2 of 3 committers (66.7%) from academic institutions
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    Scientific vocabulary similarity
    Low similarity (6.0%) to scientific vocabulary
Last synced: 9 months ago · JSON representation

Repository

R package for an empirical Bayesian statistical method to detect changes in the distribution of single-cell RNA-Seq data

Basic Info
  • Host: GitHub
  • Owner: wiscstatman
  • Language: C++
  • Default Branch: master
  • Size: 5.74 MB
Statistics
  • Stars: 0
  • Watchers: 2
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created almost 6 years ago · Last pushed about 4 years ago

https://github.com/wiscstatman/scDDboost/blob/master/ 

 About 

scDDboost is an R package to analyze changes in the distribution of single-cell expression data between two experimental conditions.
Compared to other methods that assess differential expression, scDDboost benefits uniquely from information conveyed by the clustering of cells into cellular subtypes.  Through a novel empirical Bayesian formulation it calculates gene-specific posterior probabilities that 
the marginal expression distribution is the same (or different) between the two conditions.  The implementation in scDDboost treats gene-level expression data within each condition as a mixture of negative binomial distributions.  


 Installation 

To install the R package:
```R
# install.packages("devtools")
devtools::install_github("wiscstatman/scDDboost")
```
A tutorial and examples can be found at Rpackage/vignette/ 

 Paper 

Ma, X., Korthauer, K., Kendziorski, C., and Newton, M. A. (2021). A Compositional Model To Assess Expression Changes From Single-Cell RNA-Seq Data. 
The Annals of Applied Statistics 15, no. 2: 880-901. https://doi.org/10.1214/20-AOAS1423 .  Earlier version,  bioRxiv 655795

Owner

  • Name: Michael A. Newton
  • Login: wiscstatman
  • Kind: user
  • Company: University of Wisconsin, Madison

Professor Department of Statistics and Department of Biostatistics and Medical Informatics (BMI) Chair of BMI

GitHub Events

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Committers

Last synced: over 2 years ago

All Time
  • Total Commits: 174
  • Total Committers: 3
  • Avg Commits per committer: 58.0
  • Development Distribution Score (DDS): 0.023
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
xiuyuma m****9@w****u 170
Michael A. Newton n****n@s****u 3
Michael Newton w****n@g****m 1
Committer Domains (Top 20 + Academic)
stat.wisc.edu: 1 wisc.edu: 1

Issues and Pull Requests

Last synced: about 1 year ago

All Time
  • Total issues: 0
  • Total pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Total issue authors: 0
  • Total 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
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
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Packages

  • Total packages: 1
  • Total downloads:
    • bioconductor 5,709 total
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 6
  • Total maintainers: 1
bioconductor.org: scDDboost

A compositional model to assess expression changes from single-cell rna-seq data

  • Versions: 6
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 5,709 Total
Rankings
Dependent repos count: 0.0%
Dependent packages count: 0.0%
Forks count: 19.8%
Average: 29.7%
Stargazers count: 33.2%
Downloads: 95.7%
Maintainers (1)
watsonforfun@gmail.com
Last synced: 10 months ago