Imperial College London
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DrNathanSkene

Faculty of Medicine, Department of Brain Sciences

Lecturer in Dementia Research, UK DRI Group Leader
 
 
 
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Contact

 

n.skene Website

 
 
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Location

 

515Burlington DanesHammersmith Campus

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Summary

 

Publications

Citation

BibTex format

@article{Khozoie:2021:10.1101/2021.08.16.456499,
author = {Khozoie, C and Fancy, N and Marjaneh, MM and Murphy, AE and Matthews, PM and Skene, N},
doi = {10.1101/2021.08.16.456499},
title = {scFlow: A Scalable and Reproducible Analysis Pipeline for Single-Cell RNA Sequencing Data},
url = {http://dx.doi.org/10.1101/2021.08.16.456499},
year = {2021}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - <jats:title>Abstract</jats:title><jats:p>Advances in single-cell RNA-sequencing technology over the last decade have enabled exponential increases in throughput: datasets with over a million cells are becoming commonplace. The burgeoning scale of data generation, combined with the proliferation of alternative analysis methods, led us to develop the scFlow toolkit and the nf-core/scflow pipeline for reproducible, efficient, and scalable analyses of single-cell and single-nuclei RNA-sequencing data. The scFlow toolkit provides a higher level of abstraction on top of popular single-cell packages within an R ecosystem, while the nf-core/scflow Nextflow pipeline is built within the nf-core framework to enable compute infrastructure-independent deployment across all institutions and research facilities. Here we present our flexible pipeline, which leverages the advantages of containerization and the potential of Cloud computing for easy orchestration and scaling of the analysis of large case/control datasets by even non-expert users. We demonstrate the functionality of the analysis pipeline from sparse-matrix quality control through to insight discovery with examples of analysis of four recently published public datasets and describe the extensibility of scFlow as a modular, open-source tool for single-cell and single nuclei bioinformatic analyses.</jats:p>
AU  - Khozoie,C
AU  - Fancy,N
AU  - Marjaneh,MM
AU  - Murphy,AE
AU  - Matthews,PM
AU  - Skene,N
DO  - 10.1101/2021.08.16.456499
PY  - 2021///
TI  - scFlow: A Scalable and Reproducible Analysis Pipeline for Single-Cell RNA Sequencing Data
UR  - http://dx.doi.org/10.1101/2021.08.16.456499
ER  -
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