NewWave: a scalable R/Bioconductor package for the dimensionality reduction and batch effect removal of single-cell RNA-seq data

SUMMARY: We present NewWave, a scalable R/Bioconductor package for the dimensionality reduction and batch effect removal of single-cell RNA sequencing data. To achieve scalability, NewWave uses mini-batch optimization and can work with out-of-memory data, enabling users to analyze datasets with mill...

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Autores principales: Agostinis, Federico, Romualdi, Chiara, Sales, Gabriele, Risso, Davide
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Applications Notes
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9048694/
https://www.ncbi.nlm.nih.gov/pubmed/35266509
http://dx.doi.org/10.1093/bioinformatics/btac149
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author Agostinis, Federico
Romualdi, Chiara
Sales, Gabriele
Risso, Davide
author_facet Agostinis, Federico
Romualdi, Chiara
Sales, Gabriele
Risso, Davide
author_sort Agostinis, Federico
collection PubMed
description SUMMARY: We present NewWave, a scalable R/Bioconductor package for the dimensionality reduction and batch effect removal of single-cell RNA sequencing data. To achieve scalability, NewWave uses mini-batch optimization and can work with out-of-memory data, enabling users to analyze datasets with millions of cells. AVAILABILITY AND IMPLEMENTATION: NewWave is implemented as an open-source R package available through the Bioconductor project at https://bioconductor.org/packages/NewWave/ SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-90486942022-04-29 NewWave: a scalable R/Bioconductor package for the dimensionality reduction and batch effect removal of single-cell RNA-seq data Agostinis, Federico Romualdi, Chiara Sales, Gabriele Risso, Davide Bioinformatics Applications Notes SUMMARY: We present NewWave, a scalable R/Bioconductor package for the dimensionality reduction and batch effect removal of single-cell RNA sequencing data. To achieve scalability, NewWave uses mini-batch optimization and can work with out-of-memory data, enabling users to analyze datasets with millions of cells. AVAILABILITY AND IMPLEMENTATION: NewWave is implemented as an open-source R package available through the Bioconductor project at https://bioconductor.org/packages/NewWave/ SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2022-03-10 /pmc/articles/PMC9048694/ /pubmed/35266509 http://dx.doi.org/10.1093/bioinformatics/btac149 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Notes
Agostinis, Federico
Romualdi, Chiara
Sales, Gabriele
Risso, Davide
NewWave: a scalable R/Bioconductor package for the dimensionality reduction and batch effect removal of single-cell RNA-seq data
title NewWave: a scalable R/Bioconductor package for the dimensionality reduction and batch effect removal of single-cell RNA-seq data
title_full NewWave: a scalable R/Bioconductor package for the dimensionality reduction and batch effect removal of single-cell RNA-seq data
title_fullStr NewWave: a scalable R/Bioconductor package for the dimensionality reduction and batch effect removal of single-cell RNA-seq data
title_full_unstemmed NewWave: a scalable R/Bioconductor package for the dimensionality reduction and batch effect removal of single-cell RNA-seq data
title_short NewWave: a scalable R/Bioconductor package for the dimensionality reduction and batch effect removal of single-cell RNA-seq data
title_sort newwave: a scalable r/bioconductor package for the dimensionality reduction and batch effect removal of single-cell rna-seq data
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9048694/
https://www.ncbi.nlm.nih.gov/pubmed/35266509
http://dx.doi.org/10.1093/bioinformatics/btac149
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