返回
Extracting, filtering and simulating cellular barcodes using CellBarcode tools
DOI:10.1038/s43588-024-00595-7.png)
摘要
En 中文
Identifying true DNA cellular barcodes among polymerase chain reaction and sequencing errors is challenging. Current tools are restricted in the diversity of barcode types supported or the analysis strategies implemented. As such, there is a need for more versatile and efficient tools for barcode extraction, as well as for tools to investigate which factors impact barcode detection and which filtering strategies to best apply. Here we introduce the package CellBarcode and its barcode simulation kit, CellBarcodeSim, that allows efficient and versatile barcode extraction and filtering for a range of barcode types from bulk or single-cell sequencing data using a variety of filtering strategies. Using the barcode simulation kit and biological data, we explore the technical and biological factors influencing barcode identification and provide a decision tree on how to optimize barcode identification for different barcode settings. We believe that CellBarcode and CellBarcodeSim have the capability to enhance the reproducibility and interpretation of barcode results across studies. The authors introduce two cellular barcoding tools: CellBarcode, for extracting and filtering diverse DNA barcodes from bulk and single-cell sequencing data; and CellBarcodeSim, for simulating barcoding experiments, thus enabling the investigation of the impact of biological and technical factors on barcode detection.
Keyword:
LINEAGE
TRACKING
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
18.3
论文数:
3.1K
被引数:
4.0K
机构
引用论文
Large-scale reconstruction of cell lineages using single-cell readout of transcriptomes and CRISPR-Cas9 barcodes by scGESTALT
NATURE PROTOCOLS
IF16
Paracrine signalling between intestinal epithelial and tumour cells induces a regenerative programme
ELIFE
IF0

