Synthbar: A Lightweight Tool for Adding Synthetic Barcodes to Sequencing Reads.

Area of Science:

• Genomics
• Bioinformatics

Background:

• Single-cell sequencing library preparation often incorporates nucleotide barcodes for sample or cell pooling.
• Droplet-based protocols commonly use cell barcodes (CBs), influencing downstream computational tool development.
• Microwell-based single-cell RNA sequencing (scRNA-seq) methods, like SMART, typically omit CBs, relying on unique dual indices for multiplexing.

Purpose of the Study:

• To introduce Synthbar, a novel computational tool designed to address the lack of cell barcode (CB) addition in microwell-based scRNA-seq library preparation.
• To enable the compatibility of microwell-based scRNA-seq data with computational pipelines that require CBs, such as STARsolo, zUMIs, and Alevin.

Main Methods:

• Synthbar is a lightweight, assay-agnostic tool implemented in C.
• It facilitates the addition of user-defined synthetic cell barcodes (CBs) to sequencing reads.
• The tool modifies read structures to incorporate these synthetic CBs.

Main Results:

• Synthbar successfully fills the gap for adding synthetic cell barcodes (CBs) to microwell-based scRNA-seq data.
• The tool enhances the utility of existing computational pipelines for analyzing data from methods that do not natively generate CBs.
• Synthbar is compatible with macOS and Linux operating systems.

Conclusions:

• Synthbar provides a straightforward solution for incorporating cell barcodes (CBs) into single-cell RNA sequencing (scRNA-seq) libraries prepared using microwell-based methods.
• This facilitates the broader application of advanced computational analysis tools to a wider range of scRNA-seq data.
• The availability of Synthbar promotes greater flexibility and accessibility in single-cell data analysis workflows.