Evidence map›Paper›PMID 39656909›Full record

ArticleNucleic acids research2025

QClus: a droplet filtering algorithm for enhanced snRNA-seq data quality in challenging samples.

Eloi Schmauch, Johannes Ojanen, Kyriakitsa Galani, Juho Jalkanen, Kristiina Harju, Maija Hollmén, Hannu Kokki, Jarmo Gunn, Jari Halonen, Juha Hartikainen and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nucleic acids research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Eloi SchmauchComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, MA 02139, USA.ORCID 0000-0002-2123-8777
Johannes OjanenComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, MA 02139, USA.
Kyriakitsa GalaniComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, MA 02139, USA.
Juho JalkanenMedicity Research Laboratories, University of Turku, Tykistökatu 6, 20520 Turku, Finland.
Kristiina HarjuA. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Neulaniementie 2, 70211 Kuopio, Finland.
Maija HollménMedicity Research Laboratories, University of Turku, Tykistökatu 6, 20520 Turku, Finland.
Hannu KokkiDepartment of Anesthesiology and Operative Services, Kuopio University Hospital, Puijonlaaksontie 2, 70029 KYS, Finland.
Jarmo GunnHeart Center, Turku University Hospital, Hämeentie 11, 20521 Turku, Finland.
Jari HalonenMedical School, University of Eastern Finland, Yliopistonranta 8, 70210 Kuopio, Finland.ORCID 0000-0003-3878-1546
Juha HartikainenMedical School, University of Eastern Finland, Yliopistonranta 8, 70210 Kuopio, Finland.
Tuomas KiviniemiHeart Center, Turku University Hospital, Hämeentie 11, 20521 Turku, Finland.ORCID 0000-0002-0908-3741
Pasi TaviA. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Neulaniementie 2, 70211 Kuopio, Finland.ORCID 0000-0003-2563-3616
Minna U KaikkonenA. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Neulaniementie 2, 70211 Kuopio, Finland.ORCID 0000-0001-6294-0979
Manolis KellisComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, MA 02139, USA.
Suvi Linna-KuosmanenComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, MA 02139, USA.ORCID 0000-0002-3278-2727

Funding

Aarne Koskelo FoundationAcademy of Finland 333021Antti and Tyyne Soininen FoundationFinnish Cultural FoundationFinnish Foundation for Cardiovascular ResearchMaud Kuistila Memorial FoundationOrion Research FoundationSaastamoinen FoundationSigrid Juselius FoundationUniversity of Eastern FinlandYrjö Jahnsson Foundation
6 · The paper itself

Abstract

Single-nuclei RNA sequencing remains a challenge for many human tissues, as incomplete removal of background signal masks cell-type-specific signals and interferes with downstream analyses. Here, we present Quality Clustering (QClus), a droplet filtering algorithm targeted toward challenging samples. QClus uses additional metrics, such as cell-type-specific marker gene expression, to cluster nuclei and filter empty and highly contaminated droplets, providing reliable filtering of samples with varying number of nuclei and contamination levels. In a benchmarking analysis against seven alternative methods across six datasets, consisting of 252 samples and over 1.9 million nuclei, QClus achieved the highest quality in the greatest number of samples over all evaluated quality metrics and recorded no processing failures, while robustly retaining numbers of nuclei within the expected range. QClus combines high quality, automation and robustness with flexibility and user-adjustability, catering to diverse experimental needs and datasets.

Indexed as

AlgorithmsRNA-SeqRNA, Small NuclearSequence Analysis, RNASingle-Cell AnalysisCell NucleusCluster AnalysisData AccuracyHumansSoftwareRNA, Small Nuclear

Identifiers

PMID39656909
PMCPMC11724311

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.