%0 Journal Article
%A Foerster, Leo Carl
%A Frigoli, Enrico
%A Sun, Xiaoyu
%A Hooli, Jooa Hermanni
%A Goncalves, Angela
%A Martin-Villalba, Ana
%T Umite: fast quantification of smart-seq3 libraries with improved UMI retrieval.
%J Bioinformatics
%V nn
%@ 1367-4803
%C Oxford
%I Oxford Univ. Press
%M DKFZ-2026-00354
%P nn
%D 2026
%Z #EA:A290#LA:A290# / epub
%X Commercial solutions like 10X cellranger provide robust UMI quantification for their proprietary single-cell protocols, but open methods such as Smart-seq3 lack comparable support.Here, we introduce umite, a Smart-seq3 UMI counting pipeline with a focus on speed and a light memory footprint. Unlike existing tools, umite offers efficient mismatch-tolerant UMI detection, boosting UMI retrieval by 5-15
%F PUB:(DE-HGF)16
%9 Journal Article
%$ pmid:41692984
%R 10.1093/bioinformatics/btag075
%U https://inrepo02.dkfz.de/record/309869