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BarWare: efficient software tools for barcoded single-cell genomics
BACKGROUND: Barcode-based multiplexing methods can be used to increase throughput and reduce batch effects in large single-cell genomics studies. Despite advantages in flexibility of sample collection and scale, there are additional complications in the data deconvolution steps required to assign ea...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8962164/ https://www.ncbi.nlm.nih.gov/pubmed/35346022 http://dx.doi.org/10.1186/s12859-022-04620-2 |
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author | Swanson, Elliott Reading, Julian Graybuck, Lucas T. Skene, Peter J. |
author_facet | Swanson, Elliott Reading, Julian Graybuck, Lucas T. Skene, Peter J. |
author_sort | Swanson, Elliott |
collection | PubMed |
description | BACKGROUND: Barcode-based multiplexing methods can be used to increase throughput and reduce batch effects in large single-cell genomics studies. Despite advantages in flexibility of sample collection and scale, there are additional complications in the data deconvolution steps required to assign each cell to their originating samples. RESULTS: To meet computational needs for efficient sample deconvolution, we developed the tools BarCounter and BarMixer that compute barcode counts and deconvolute mixed single-cell data into sample-specific files, respectively. Together, these tools are implemented as the BarWare pipeline to support demultiplexing from large sequencing projects with many wells of hashed 10x Genomics scRNA-seq data. CONCLUSIONS: BarWare is a modular set of tools linked by shell scripting: BarCounter, a computationally efficient barcode sequence quantification tool implemented in C; and BarMixer, an R package for identification of barcoded populations, merging barcoded data from multiple wells, and quality-control reporting related to scRNA-seq data. These tools and a self-contained implementation of the pipeline are freely available for non-commercial use at https://github.com/AllenInstitute/BarWare-pipeline. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-022-04620-2. |
format | Online Article Text |
id | pubmed-8962164 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-89621642022-03-30 BarWare: efficient software tools for barcoded single-cell genomics Swanson, Elliott Reading, Julian Graybuck, Lucas T. Skene, Peter J. BMC Bioinformatics Software BACKGROUND: Barcode-based multiplexing methods can be used to increase throughput and reduce batch effects in large single-cell genomics studies. Despite advantages in flexibility of sample collection and scale, there are additional complications in the data deconvolution steps required to assign each cell to their originating samples. RESULTS: To meet computational needs for efficient sample deconvolution, we developed the tools BarCounter and BarMixer that compute barcode counts and deconvolute mixed single-cell data into sample-specific files, respectively. Together, these tools are implemented as the BarWare pipeline to support demultiplexing from large sequencing projects with many wells of hashed 10x Genomics scRNA-seq data. CONCLUSIONS: BarWare is a modular set of tools linked by shell scripting: BarCounter, a computationally efficient barcode sequence quantification tool implemented in C; and BarMixer, an R package for identification of barcoded populations, merging barcoded data from multiple wells, and quality-control reporting related to scRNA-seq data. These tools and a self-contained implementation of the pipeline are freely available for non-commercial use at https://github.com/AllenInstitute/BarWare-pipeline. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-022-04620-2. BioMed Central 2022-03-27 /pmc/articles/PMC8962164/ /pubmed/35346022 http://dx.doi.org/10.1186/s12859-022-04620-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/ 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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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 Swanson, Elliott Reading, Julian Graybuck, Lucas T. Skene, Peter J. BarWare: efficient software tools for barcoded single-cell genomics |
title | BarWare: efficient software tools for barcoded single-cell genomics |
title_full | BarWare: efficient software tools for barcoded single-cell genomics |
title_fullStr | BarWare: efficient software tools for barcoded single-cell genomics |
title_full_unstemmed | BarWare: efficient software tools for barcoded single-cell genomics |
title_short | BarWare: efficient software tools for barcoded single-cell genomics |
title_sort | barware: efficient software tools for barcoded single-cell genomics |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8962164/ https://www.ncbi.nlm.nih.gov/pubmed/35346022 http://dx.doi.org/10.1186/s12859-022-04620-2 |
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