CleanBar: a versatile demultiplexing tool for split-and-pool barcoding in single-cell omics

Area of Science:

• Microbial Ecology
• Genomics
• Bioinformatics

Background:

• Split-and-pool barcoding is crucial for single-cell omics, but lacks a universal bioinformatic tool for demultiplexing.
• Existing methods struggle with variations in barcode position, linker length, and ligation errors.

Purpose of the Study:

• To develop a flexible and accurate bioinformatic tool for demultiplexing single cells barcoded with sequential ligations.
• To address limitations in current tools for analyzing microbial single-cell genomics data.

Main Methods:

• Development of CleanBar, a novel bioinformatic tool for demultiplexing sequentially ligated barcodes.
• Application of CleanBar with the Atrandi platform and PacBio sequencing for microbial single-cell genomics.
• Testing CleanBar's ability to handle barcode variations and ligation errors.

Main Results:

• CleanBar accurately demultiplexes reads, accommodating variations in barcode positions and linker lengths.
• The tool successfully prevents misclassification of natural barcode-like sequences and handles ligation errors.
• Single-cell genomics of *Klebsiella* strains infected with phages revealed infection heterogeneity and enabled phage copy number estimation.

Conclusions:

• CleanBar is an efficient, adaptable, and precise tool for microbial single-cell genomics.
• Combined with the Atrandi platform and PacBio sequencing, CleanBar enhances high-throughput analysis of microbial ecology and evolution.
• The tool facilitates deeper understanding of phage-bacteria interactions at the single-cell level.