UMI-nea: a fast, robust tool for reference-free UMI deduplication and accurate quantification.

ABSTRACT:

Motivation

One of the key applications of Unique Molecular Identifiers (UMIs) in high-throughput sequencing is to correct for PCR amplification bias and removal of PCR duplicates, thereby improving quantification in DNA-seq and RNA-seq applications. Accurately grouping error-bearing UMIs that originate from the same input molecule through a UMI deduplication method is a critical step in this process. However, many existing UMI deduplication tools rely on simple Hamming distance comparisons or suboptimal clustering algorithms, often resulting in erroneous UMI groupings, particularly in error-prone long-read sequencing or ultra-high-depth short-read sequencing.

Results

We introduce UMI-nea, a tool that utilizes Levenshtein distance comparisons and a novel clustering approach t

SUBMITTER: Deng J 

PROVIDER: S-EPMC12453673 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature