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Rare Event Detection Using Error-corrected DNA and RNA Sequencing
Published on: August 3, 2018
RAD: A Read-structure Agnostic Demultiplexer for Single-Cell Long-Read Sequencing and Analysis
Chinmay M Vaidya1,2, Margaret C Carpenter1, Leena Abdullah2,3
1Thayer School of Engineering, Dartmouth, Hanover, NH.
Biorxiv : the Preprint Server for Biology
|June 12, 2026
Summary
We developed RAD, a new computational tool for single-cell long-read sequencing data. RAD accurately demultiplexes and corrects barcodes, improving analysis of transcriptomes and spatial transcriptomics.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- Single-cell long-read sequencing (LRS) offers full transcript analysis but faces computational hurdles due to high error rates and complex read structures.
- Existing methods often require custom workflows for accurate cell barcode extraction and error correction.
Purpose of the Study:
- To introduce RAD (Read-structure Agnostic Demultiplexer), an error-robust computational tool designed to overcome LRS data challenges.
- To enable efficient and accurate demultiplexing and barcode correction for diverse LRS data, including complex layouts.
Main Methods:
- RAD allows users to define read structures, including adapter sequences and barcode positions, for flexible element extraction.
- It incorporates efficient barcode correction strategies, supporting scenarios with known or unknown barcode whitelists and integration with short-read data.
Main Results:
- RAD demonstrates superior speed and significantly higher sensitivity compared to existing pipelines in both synthetic and real-world benchmarks, with comparable precision.
- The tool successfully applied to high-definition long-read spatial transcriptomic data.
Conclusions:
- RAD provides a robust and efficient solution for demultiplexing and error correction in single-cell long-read sequencing.
- Its application to spatial transcriptomics enables advanced single-cell and spatial analyses, such as B cell isotype and secretion state characterization.
