https://github.com/tallulandrews/M3Drop

https://github.com/tallulandrews/M3Drop

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

Last synced: about 1 month ago
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• Host: GitHub
• URL: https://github.com/tallulandrews/M3Drop
• Owner: tallulandrews
• Created: 2016-07-13T10:22:59.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2024-03-04T09:46:01.000Z (9 months ago)
• Last Synced: 2024-11-04T16:06:25.074Z (about 1 month ago)
• Topics: human-cell-atlas, rna-seq, single-cell, single-cell-rna-seq
• Language: R
• Size: 5.51 MB
• Stars: 29
• Watchers: 5
• Forks: 9
• Open Issues: 4
• Metadata Files:
  • Readme: README

Awesome Lists containing this project

• awesome-single-cell - M3Drop - [R] - Michaelis-Menten Modelling of Dropouts for scRNASeq. (Software packages / RNA-seq)

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