细胞条形码是一种谱系追踪方法,可将可遗传的合成条形码与高通量测序相结合,能够在一系列生物环境中准确追踪细胞谱系。最近的研究通过将谱系信息纳入单细胞或空间转录组学读数来扩展这些方法。利用这些数据集中丰富的生物信息需要专用的计算工具进行数据集预处理和分析。这里,我们介绍BARtab,一个可移植和可扩展的Nextflow管道,和bartools,一个开源的R包,旨在提供一个集成的端到端细胞条形码分析工具包。BARtab和bartools包含简化提取的方法,质量控制,分析,和从人口水平可视化谱系条形码,单细胞,和空间转录组学实验。我们展示了我们的集成BARtab和bartools工作流程的效用,通过样本批量分析,单细胞,和包含细胞条形码信息的空间转录组学实验。
Cellular barcoding is a lineage-tracing methodology that couples heritable synthetic barcodes to high-throughput sequencing, enabling the accurate tracing of cell lineages across a range of biological contexts. Recent studies have extended these methods by incorporating lineage information into single-cell or spatial transcriptomics readouts. Leveraging the rich biological information within these datasets requires dedicated computational tools for dataset pre-processing and analysis. Here, we present BARtab, a portable and scalable Nextflow pipeline, and bartools, an open-source R package, designed to provide an integrated end-to-end cellular barcoding analysis toolkit. BARtab and bartools contain methods to simplify the extraction, quality control, analysis, and visualization of lineage barcodes from population-level, single-cell, and spatial transcriptomics experiments. We showcase the utility of our integrated BARtab and bartools workflow via the analysis of exemplar bulk, single-cell, and spatial transcriptomics experiments containing cellular barcoding information.