Researchers Released Nailpolish Tool for Sequencing Data
The new method improves long-read sequencing accuracy by deduplicating reads without a reference genome.
Updated on Sept. 29, 2026 in Biotech
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Researchers have released Nailpolish, a tool designed to perform error correction and deduplication on UMI-tagged long-read sequencing data. The software uses partial order alignment to improve sequence quality and has been validated across eleven datasets.
Why it matters
Long-read sequencing typically suffers from elevated error rates and distortion caused by PCR duplicates, which can compromise data quantification. Nailpolish addresses these issues by identifying false duplicates and refining read accuracy.
The tool uses partial order alignment to generate consensus sequences from 11 datasets spanning bulk, single-cell, spatial, and targeted protocols. It outperformed existing deduplication tools by isolating errors and false duplicates generated by UMI collisions.
The players
Oxford Nanopore Technologies
A developer of nanopore-based electronic systems for analysis of DNA and RNA.
Pacific Biosciences
A provider of long-read sequencing platforms that identify genetic variation.
The details
Nailpolish operates by identifying UMI-tagged long reads—DNA sequences labeled with unique molecular identifiers to track individual molecules—that often contain errors during PCR amplification. The tool employs partial order alignment, a process that constructs a graph of sequence alignments to determine the most accurate consensus sequence. By separating false duplicates resulting from UMI collisions, it effectively reduces per-read error rates in datasets produced by Oxford Nanopore Technologies and Pacific Biosciences.
Timeline
September 25, 2026: Nailpolish was released via a research paper preprint.
The Tech Race
The release of Nailpolish marks the latest attempt to improve long-read sequence fidelity as Oxford Nanopore and Pacific Biosciences continue to compete for higher accuracy benchmarks. It serves as a necessary middleware layer to counteract the error rates inherent in current long-read sequencing workflows.
Researchers working with bulk, single-cell, or spatial sequencing data can now incorporate Nailpolish into their pipelines to reduce PCR-induced distortion. The tool is currently available via a research preprint for those needing to refine sequencing quality immediately.
The takeaway
Nailpolish provides a computational solution to long-read data noise that does not rely on reference genomes. Watch for upcoming benchmarks in the research paper to see how the software scales as sequencing throughput increases.
Further reading
For more on the latest methods in genetic analysis, visit our Biotech section.
More information
Read the complete research paper preprint for technical specifications.
Source note: This article includes information reported by Biorxiv.
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