https://github.com/fperraudeau/singlecellworkflow
Tutorial for the analysis of scRNA-seq data in R
https://github.com/fperraudeau/singlecellworkflow
bioconductor clustering differential-expression dimensionality-reduction lineage normalization r single-cell single-cell-rna-seq workflow
Last synced: 28 days ago
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Tutorial for the analysis of scRNA-seq data in R
- Host: GitHub
- URL: https://github.com/fperraudeau/singlecellworkflow
- Owner: fperraudeau
- Created: 2017-05-03T20:32:31.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2018-08-28T21:51:43.000Z (about 7 years ago)
- Last Synced: 2025-01-06T16:54:19.506Z (9 months ago)
- Topics: bioconductor, clustering, differential-expression, dimensionality-reduction, lineage, normalization, r, single-cell, single-cell-rna-seq, workflow
- Language: TeX
- Homepage:
- Size: 148 MB
- Stars: 17
- Watchers: 7
- Forks: 6
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
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README
# Bioconductor workflow for single-cell RNA sequencing: Normalization, dimensionality reduction, clustering, and lineage inference
[](https://zenodo.org/badge/latestdoi/90190906)
This repository is designed to provide a tutorial for the analysis of scRNA-seq data in R. It covers four main steps: (1) dimensionality reduction accounting for zero inflation and over-dispersion and adjusting for gene and cell-level covariates; (2) robust and stable cell clustering using resampling-based sequential ensemble clustering; (3) inference of cell lineages and ordering of the cells by developmental progression along lineages; and (4) DE analysis along lineages. The workflow is general and flexible, allowing the user to sustitute the statistical method used in each step by a different method. We hope our proposed workflow will ease technical aspects of scRNA-seq data analysis and help with the discovery of novel biological insights.
## Dependencies
To be able to run [workflow.Rmd](https://github.com/fperraudeau/singlecellworkflow/blob/master/workflow/workflow.Rmd), you need
### Bioconductor
- BiocParallel
- clusterExperiment
- scone
- zinbwave
### GitHub
- slingshot (https://github.com/kstreet13/slingshot)
### CRAN
- doParallel
- gam
- RColorBrewer
Note that you need the devel versions
of the Bioconductor packages `scone (>=1.1.2)`, `zinbwave (>=0.99.6)`, and `clusterExperiment (>=1.3.2)`. We recommend running Bioconductor 3.6 (currently the devel version; see https://www.bioconductor.org/developers/how-to/useDevel/).