Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Swanson, Elliott, Reading, Julian, Graybuck, Lucas T., Skene, Peter J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
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
_version_ 1784677738732322816
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
work_keys_str_mv AT swansonelliott barwareefficientsoftwaretoolsforbarcodedsinglecellgenomics
AT readingjulian barwareefficientsoftwaretoolsforbarcodedsinglecellgenomics
AT graybucklucast barwareefficientsoftwaretoolsforbarcodedsinglecellgenomics
AT skenepeterj barwareefficientsoftwaretoolsforbarcodedsinglecellgenomics