Data

Tools

Indexes

Applications

Experiments

Open Source Science

M3Drop

https://github.com/tallulandrews/m3drop

Science Score: 36.0%

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

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ○
    .zenodo.json file
  • ✓
    DOI references
    Found 4 DOI reference(s) in README
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    2 of 10 committers (20.0%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (6.7%) to scientific vocabulary

Keywords

human-cell-atlas rna-seq single-cell single-cell-rna-seq

Keywords from Contributors

bioconductor-package genomics gene bioinformatics statistical-analysis methylation genome-biology looking-for-maintainer core-services peak-detection
Last synced: 6 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: tallulandrews
  • Language: R
  • Default Branch: master
  • Size: 5.51 MB
Statistics
  • Stars: 30
  • Watchers: 5
  • Forks: 9
  • Open Issues: 4
  • Releases: 0
Topics
human-cell-atlas rna-seq single-cell single-cell-rna-seq
Created over 9 years ago · Last pushed almost 2 years ago
Metadata Files
Readme

README 

# M3Drop - Michaelis-Menten Modelling of Dropouts for scRNASeq

This is an R package providing functions for fitting a modified Michaelis-Menten (MM) equation to the pattern of dropouts observed in a single-cell sequencing experiment. As well as the Depth-Adjusted Negative Binomial (DANB) model which is tailored for datasets quantified using unique molecular identifiers (UMIs).

Functions are provided for fitting each model as well as performing dropout-based feature selection. These can be used to reduce technical noise in downstream analyses such as clustering or pseudotime analysis.

Update 2023-02-16 :
New functions: NBumiPearsonResiduals and NBumiPearsonResidualsApprox enable the calculation of pearson residuals using the depth-adjusted negative binomial model. Pearson residuals have recently been suggested as an alternative normalization strategy for single-cell RNAseq data see: https://genomebiology.biomedcentral.com/articles/10.1186/s13059-021-02451-7#S

For comparison, the algorithm presented in Brennecke et al (2015) for detection of significantly highly variable genes is included.

## Installation :
```r
require("remotes")
install_github('tallulandrews/M3Drop')
```
OR
```r
if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("M3Drop")
```
Example Data:
```r
require("remotes")
install_github('tallulandrews/M3DExampleData')
```
OR

```r
if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("M3DExapleData")
```
Read More: DOI: 10.1101/065094

## Citation:
Amdrews, TS and Hemberg, M. (2018) M3Drop:dropout-based feature selection for scRNASeq. Bioinformatics, bty1044. https://doi.org/10.1093/bioinformatics/bty1044

Owner

  • Login: tallulandrews
  • Kind: user

GitHub Events

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

Committers

Last synced: over 1 year ago

All Time
  • Total Commits: 268
  • Total Committers: 10
  • Avg Commits per committer: 26.8
  • Development Distribution Score (DDS): 0.09
Past Year
  • Commits: 1
  • Committers: 1
  • Avg Commits per committer: 1.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Tallulah Andrews t****6@s****k 244
Vladimir Kiselev v****v@g****m 5
Herve Pages h****s@f****g 4
Tallulah Andrews t****s@g****m 4
Leon Fodoulian 3****n 4
Hervé Pagès h****s@f****g 2
hpages@fhcrc.org h****s@f****g@b****8 2
Jens Preußner j****r@m****e 1
Martin Morgan m****n@f****g 1
mtmorgan@fhcrc.org m****n@f****g@b****8 1
Committer Domains (Top 20 + Academic)
fhcrc.org: 4 mpi-bn.mpg.de: 1 fredhutch.org: 1 sanger.ac.uk: 1

Issues and Pull Requests

Last synced: 7 months ago

All Time
  • Total issues: 14
  • Total pull requests: 2
  • Average time to close issues: 10 months
  • Average time to close pull requests: 10 days
  • Total issue authors: 13
  • Total pull request authors: 1
  • Average comments per issue: 0.71
  • Average comments per pull request: 0.0
  • Merged pull requests: 2
  • 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
  • tallulandrews (2)
  • sinanassiri (1)
  • MJ-Yang (1)
  • haircell (1)
  • Hemantcnaik (1)
  • flying-sheep (1)
  • MingBit (1)
  • giorgosminas (1)
  • lzygenomics (1)
  • AswinSSoman (1)
  • lucygarner (1)
  • saketkc (1)
Pull Request Authors
  • leonfodoulian (2)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • bioconductor 55,081 total
  • Total dependent packages: 1
  • Total dependent repositories: 0
  • Total versions: 5
  • Total maintainers: 1
bioconductor.org: M3Drop

Michaelis-Menten Modelling of Dropouts in single-cell RNASeq

  • Versions: 5
  • Dependent Packages: 1
  • Dependent Repositories: 0
  • Downloads: 55,081 Total
Rankings
Dependent repos count: 0.0%
Dependent packages count: 0.0%
Stargazers count: 6.2%
Forks count: 6.8%
Average: 6.9%
Downloads: 21.2%
Maintainers (1)
tallulandrews@gmail.com
Last synced: 6 months ago