Unique Molecular Identifiers Don’t Need to be Unique: A Collision-Aware Estimator for RNA-Seq Quantification

RNA-sequencing (RNA-seq) relies on Unique Molecular Identifiers (UMIs) to accurately quantify gene expression after PCR amplification. Longer UMIs minimize collisions-where two distinct transcripts are assigned the same UMI-at the expense of increased sequencing and synthesis costs. However, it is not clear how long UMIs need to be in practice, especially given the nonuniformity of the empirical UMI distribution. In this work, we develop a method-of-moments estimator that accounts for UMI collisions, accurately quantifying gene expression and preserving downstream biological insights. We show that UMIs need not be unique: shorter UMIs can be used with a more sophisticated estimator.

Authors

Institutions

Publication Details

Journal
Journal of Computational Biology
Published
2026-09-15
DOI
https://doi.org/10.1177/15578666261477771
Primary Topic
Molecular Biology Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

Unique Molecular Identifiers Don’t Need to be Unique: A Collision-Aware Estimator for RNA-Seq Quantification

Rafael A. Irizarry, Tavor Z. Baharav, Dylan Agyemang
Journal of Computational Biology
Molecular Biology Techniques and Applications
article

Unique Molecular Identifiers Don’t Need to be Unique: A Collision-Aware Estimator for RNA-Seq Quantification

Rafael A. Irizarry, Tavor Z. Baharav, Dylan Agyemang
article en

Abstract

RNA-sequencing (RNA-seq) relies on Unique Molecular Identifiers (UMIs) to accurately quantify gene expression after PCR amplification. Longer UMIs minimize collisions-where two distinct transcripts are assigned the same UMI-at the expense of increased sequencing and synthesis costs. However, it is not clear how long UMIs need to be in practice, especially given the nonuniformity of the empirical UMI distribution. In this work, we develop a method-of-moments estimator that accounts for UMI collisions, accurately quantifying gene expression and preserving downstream biological insights. We show that UMIs need not be unique: shorter UMIs can be used with a more sophisticated estimator.

Journal of Computational Biology
Broad Institute (US), University of North Carolina at Chapel Hill (US), Harvard University (US), Dana-Farber Cancer Institute (US)
National Human Genome Research Institute, National Institute of General Medical Sciences
Openalex Percentile: Top 99%
Molecular Biology Techniques and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Unique Molecular Identifiers Don’t Need to be Unique: A Collision-Aware Estimator for RNA-Seq Quantification — Rafael A. Irizarry, Tavor Z. Baharav, et al. · Journal of Computational Biology (2026) | TGRS Research Map | TGRS