BarWare: efficient software tools for barcoded single-cell genomics
Abstract 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 a...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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BMC
2022-03-01
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| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12859-022-04620-2 |
| _version_ | 1819052134992183296 |
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| author | Elliott Swanson Julian Reading Lucas T. Graybuck Peter J. Skene |
| author_facet | Elliott Swanson Julian Reading Lucas T. Graybuck Peter J. Skene |
| author_sort | Elliott Swanson |
| collection | DOAJ |
| description | Abstract 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 . |
| first_indexed | 2024-12-21T12:15:01Z |
| format | Article |
| id | doaj.art-21179aa92949406b80b4c94dfe7b6c4c |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-12-21T12:15:01Z |
| publishDate | 2022-03-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj.art-21179aa92949406b80b4c94dfe7b6c4c2022-12-21T19:04:28ZengBMCBMC Bioinformatics1471-21052022-03-0123111410.1186/s12859-022-04620-2BarWare: efficient software tools for barcoded single-cell genomicsElliott Swanson0Julian Reading1Lucas T. Graybuck2Peter J. Skene3Allen Institute for ImmunologyAllen Institute for ImmunologyAllen Institute for ImmunologyAllen Institute for ImmunologyAbstract 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 .https://doi.org/10.1186/s12859-022-04620-2Single-cell RNA-seqCell hashingDemultiplexingGenomics |
| spellingShingle | Elliott Swanson Julian Reading Lucas T. Graybuck Peter J. Skene BarWare: efficient software tools for barcoded single-cell genomics BMC Bioinformatics Single-cell RNA-seq Cell hashing Demultiplexing 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 | Single-cell RNA-seq Cell hashing Demultiplexing Genomics |
| url | https://doi.org/10.1186/s12859-022-04620-2 |
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