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 eac...
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| Published in: | BMC bioinformatics Vol. 23; no. 1; pp. 106 - 14 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
London
BioMed Central
27.03.2022
BioMed Central Ltd Springer Nature B.V BMC |
| Subjects: | |
| ISSN: | 1471-2105, 1471-2105 |
| Online Access: | Get full text |
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| Summary: | 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
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| ISSN: | 1471-2105 1471-2105 |
| DOI: | 10.1186/s12859-022-04620-2 |