Cargando…
WASP: a versatile, web-accessible single cell RNA-Seq processing platform
BACKGROUND: The technology of single cell RNA sequencing (scRNA-seq) has gained massively in popularity as it allows unprecedented insights into cellular heterogeneity as well as identification and characterization of (sub-)cellular populations. Furthermore, scRNA-seq is almost ubiquitously applicab...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7977290/ https://www.ncbi.nlm.nih.gov/pubmed/33736596 http://dx.doi.org/10.1186/s12864-021-07469-6 |
_version_ | 1783667102408769536 |
---|---|
author | Hoek, Andreas Maibach, Katharina Özmen, Ebru Vazquez-Armendariz, Ana Ivonne Mengel, Jan Philipp Hain, Torsten Herold, Susanne Goesmann, Alexander |
author_facet | Hoek, Andreas Maibach, Katharina Özmen, Ebru Vazquez-Armendariz, Ana Ivonne Mengel, Jan Philipp Hain, Torsten Herold, Susanne Goesmann, Alexander |
author_sort | Hoek, Andreas |
collection | PubMed |
description | BACKGROUND: The technology of single cell RNA sequencing (scRNA-seq) has gained massively in popularity as it allows unprecedented insights into cellular heterogeneity as well as identification and characterization of (sub-)cellular populations. Furthermore, scRNA-seq is almost ubiquitously applicable in medical and biological research. However, these new opportunities are accompanied by additional challenges for researchers regarding data analysis, as advanced technical expertise is required in using bioinformatic software. RESULTS: Here we present WASP, a software for the processing of Drop-Seq-based scRNA-Seq data. Our software facilitates the initial processing of raw reads generated with the ddSEQ or 10x protocol and generates demultiplexed gene expression matrices including quality metrics. The processing pipeline is realized as a Snakemake workflow, while an R Shiny application is provided for interactive result visualization. WASP supports comprehensive analysis of gene expression matrices, including detection of differentially expressed genes, clustering of cellular populations and interactive graphical visualization of the results. The R Shiny application can be used with gene expression matrices generated by the WASP pipeline, as well as with externally provided data from other sources. CONCLUSIONS: With WASP we provide an intuitive and easy-to-use tool to process and explore scRNA-seq data. To the best of our knowledge, it is currently the only freely available software package that combines pre- and post-processing of ddSEQ- and 10x-based data. Due to its modular design, it is possible to use any gene expression matrix with WASP’s post-processing R Shiny application. To simplify usage, WASP is provided as a Docker container. Alternatively, pre-processing can be accomplished via Conda, and a standalone version for Windows is available for post-processing, requiring only a web browser. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-021-07469-6. |
format | Online Article Text |
id | pubmed-7977290 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-79772902021-03-22 WASP: a versatile, web-accessible single cell RNA-Seq processing platform Hoek, Andreas Maibach, Katharina Özmen, Ebru Vazquez-Armendariz, Ana Ivonne Mengel, Jan Philipp Hain, Torsten Herold, Susanne Goesmann, Alexander BMC Genomics Software BACKGROUND: The technology of single cell RNA sequencing (scRNA-seq) has gained massively in popularity as it allows unprecedented insights into cellular heterogeneity as well as identification and characterization of (sub-)cellular populations. Furthermore, scRNA-seq is almost ubiquitously applicable in medical and biological research. However, these new opportunities are accompanied by additional challenges for researchers regarding data analysis, as advanced technical expertise is required in using bioinformatic software. RESULTS: Here we present WASP, a software for the processing of Drop-Seq-based scRNA-Seq data. Our software facilitates the initial processing of raw reads generated with the ddSEQ or 10x protocol and generates demultiplexed gene expression matrices including quality metrics. The processing pipeline is realized as a Snakemake workflow, while an R Shiny application is provided for interactive result visualization. WASP supports comprehensive analysis of gene expression matrices, including detection of differentially expressed genes, clustering of cellular populations and interactive graphical visualization of the results. The R Shiny application can be used with gene expression matrices generated by the WASP pipeline, as well as with externally provided data from other sources. CONCLUSIONS: With WASP we provide an intuitive and easy-to-use tool to process and explore scRNA-seq data. To the best of our knowledge, it is currently the only freely available software package that combines pre- and post-processing of ddSEQ- and 10x-based data. Due to its modular design, it is possible to use any gene expression matrix with WASP’s post-processing R Shiny application. To simplify usage, WASP is provided as a Docker container. Alternatively, pre-processing can be accomplished via Conda, and a standalone version for Windows is available for post-processing, requiring only a web browser. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-021-07469-6. BioMed Central 2021-03-18 /pmc/articles/PMC7977290/ /pubmed/33736596 http://dx.doi.org/10.1186/s12864-021-07469-6 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Software Hoek, Andreas Maibach, Katharina Özmen, Ebru Vazquez-Armendariz, Ana Ivonne Mengel, Jan Philipp Hain, Torsten Herold, Susanne Goesmann, Alexander WASP: a versatile, web-accessible single cell RNA-Seq processing platform |
title | WASP: a versatile, web-accessible single cell RNA-Seq processing platform |
title_full | WASP: a versatile, web-accessible single cell RNA-Seq processing platform |
title_fullStr | WASP: a versatile, web-accessible single cell RNA-Seq processing platform |
title_full_unstemmed | WASP: a versatile, web-accessible single cell RNA-Seq processing platform |
title_short | WASP: a versatile, web-accessible single cell RNA-Seq processing platform |
title_sort | wasp: a versatile, web-accessible single cell rna-seq processing platform |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7977290/ https://www.ncbi.nlm.nih.gov/pubmed/33736596 http://dx.doi.org/10.1186/s12864-021-07469-6 |
work_keys_str_mv | AT hoekandreas waspaversatilewebaccessiblesinglecellrnaseqprocessingplatform AT maibachkatharina waspaversatilewebaccessiblesinglecellrnaseqprocessingplatform AT ozmenebru waspaversatilewebaccessiblesinglecellrnaseqprocessingplatform AT vazquezarmendarizanaivonne waspaversatilewebaccessiblesinglecellrnaseqprocessingplatform AT mengeljanphilipp waspaversatilewebaccessiblesinglecellrnaseqprocessingplatform AT haintorsten waspaversatilewebaccessiblesinglecellrnaseqprocessingplatform AT heroldsusanne waspaversatilewebaccessiblesinglecellrnaseqprocessingplatform AT goesmannalexander waspaversatilewebaccessiblesinglecellrnaseqprocessingplatform |