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BarWare:用于条码单细胞基因组学的高效软件工具。

BarWare: efficient software tools for barcoded single-cell genomics.

机构信息

Allen Institute for Immunology, Seattle, WA, USA.

Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA.

出版信息

BMC Bioinformatics. 2022 Mar 27;23(1):106. doi: 10.1186/s12859-022-04620-2.

DOI:10.1186/s12859-022-04620-2
PMID:35346022
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8962164/
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 .

摘要

背景

基于条形码的多重方法可用于增加高通量和减少大型单细胞基因组学研究中的批次效应。尽管在样本采集和规模的灵活性方面具有优势,但在将每个细胞分配到其原始样本所需的数据解卷积步骤中存在额外的复杂性。

结果

为了满足高效样本解卷积的计算需求,我们开发了 BarCounter 和 BarMixer 这两个工具,它们分别计算条形码计数和解卷积混合单细胞数据成特定于样本的文件。这两个工具共同构成了 BarWare 管道,以支持从具有许多哈希 10x Genomics scRNA-seq 数据孔的大型测序项目中进行多路复用。

结论

BarWare 是一组通过 shell 脚本链接的模块化工具:BarCounter 是一种用 C 语言实现的计算高效的条形码序列定量工具;BarMixer 是一个用于识别条形码群体、合并来自多个孔的条形码数据以及与 scRNA-seq 数据相关的质量控制报告的 R 包。这些工具和管道的自包含实现可在非商业用途上免费获得,网址为 https://github.com/AllenInstitute/BarWare-pipeline。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6aa5/8962164/8d171b923341/12859_2022_4620_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6aa5/8962164/01fa95bab969/12859_2022_4620_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6aa5/8962164/720b7d596bda/12859_2022_4620_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6aa5/8962164/8d171b923341/12859_2022_4620_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6aa5/8962164/01fa95bab969/12859_2022_4620_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6aa5/8962164/720b7d596bda/12859_2022_4620_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6aa5/8962164/8d171b923341/12859_2022_4620_Fig3_HTML.jpg

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本文引用的文献

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2
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Cell. 2021 Jun 24;184(13):3573-3587.e29. doi: 10.1016/j.cell.2021.04.048. Epub 2021 May 31.
3
Highly multiplexed single-cell RNA-seq by DNA oligonucleotide tagging of cellular proteins.通过细胞蛋白的 DNA 寡核苷酸标记进行高度多重化的单细胞 RNA-seq。
纵向多组学免疫分析揭示健康成年人中与年龄相关的免疫细胞动态变化。
bioRxiv. 2024 Sep 14:2024.09.10.612119. doi: 10.1101/2024.09.10.612119.
4
Trimodal single-cell profiling reveals a novel pediatric CD8αα T cell subset and broad age-related molecular reprogramming across the T cell compartment.三模态单细胞分析揭示了一种新型儿科 CD8αα T 细胞亚群,并广泛揭示了 T 细胞区室中与年龄相关的分子重编程。
Nat Immunol. 2023 Nov;24(11):1947-1959. doi: 10.1038/s41590-023-01641-8. Epub 2023 Oct 16.
Nat Biotechnol. 2020 Jan;38(1):35-38. doi: 10.1038/s41587-019-0372-z. Epub 2019 Dec 23.
4
Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression.使用正则化负二项式回归进行单细胞 RNA-seq 数据的归一化和方差稳定化。
Genome Biol. 2019 Dec 23;20(1):296. doi: 10.1186/s13059-019-1874-1.
5
Cell Hashing with barcoded antibodies enables multiplexing and doublet detection for single cell genomics.细胞条码抗体标记技术可实现单细胞基因组学的多重检测和双细胞检测。
Genome Biol. 2018 Dec 19;19(1):224. doi: 10.1186/s13059-018-1603-1.
6
Massively parallel digital transcriptional profiling of single cells.大规模平行数字化单细胞转录组分析。
Nat Commun. 2017 Jan 16;8:14049. doi: 10.1038/ncomms14049.
7
Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets.利用纳升液滴对单个细胞进行高度并行的全基因组表达谱分析。
Cell. 2015 May 21;161(5):1202-1214. doi: 10.1016/j.cell.2015.05.002.
8
Identification of an evolutionarily conserved transcriptional signature of CD8 memory differentiation that is shared by T and B cells.鉴定出一种T细胞和B细胞共有的、进化上保守的CD8记忆分化转录特征。
J Immunol. 2008 Aug 1;181(3):1859-68. doi: 10.4049/jimmunol.181.3.1859.