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Updated: Sep 28, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
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BarWare: efficient software tools for barcoded single-cell genomics.

Elliott Swanson1,2, Julian Reading1, Lucas T Graybuck3

  • 1Allen Institute for Immunology, Seattle, WA, USA.

BMC Bioinformatics
|March 29, 2022
PubMed
Summary
This summary is machine-generated.

We developed BarWare, a computational pipeline for demultiplexing single-cell RNA sequencing data. This tool efficiently deconvolutes pooled samples, improving large-scale genomics studies.

Keywords:
Cell hashingDemultiplexingGenomicsSingle-cell RNA-seq

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Barcode-based multiplexing enhances throughput and reduces batch effects in large single-cell genomics studies.
  • Challenges exist in deconvoluting multiplexed data to assign cells to their original samples.

Purpose of the Study:

  • To develop computational tools for efficient sample deconvolution in large-scale single-cell genomics.
  • To address the need for accurate cell origin assignment in multiplexed scRNA-seq data.

Main Methods:

  • Developed BarWare, a pipeline comprising BarCounter and BarMixer tools.
  • BarCounter quantifies barcode counts; BarMixer deconvolutes mixed single-cell data.
  • Utilized shell scripting for modular tool integration.

Main Results:

  • BarWare enables efficient demultiplexing of 10x Genomics scRNA-seq data from multiple wells.
  • The pipeline supports large sequencing projects with hashed samples.
  • Provides sample-specific files after deconvolution.

Conclusions:

  • BarWare offers a modular solution for barcode sequence quantification and data deconvolution.
  • Includes BarCounter (C implementation) and BarMixer (R package).
  • Freely available for non-commercial use, facilitating large-scale single-cell genomics research.