Evidence map›Paper›PMID 39838291›Full record

ArticleBMC bioinformatics2025

ClearFinder: a Python GUI for annotating cells in cleared mouse brain.

Stefan Pastore, Philipp Hillenbrand, Nils Molnar, Irina Kovlyagina, Monika Chanu Chongtham, Stanislav Sys, Beat Lutz, Margarita Tevosian, Susanne Gerber

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PubMed Full text at PMC Publisher
In one paragraph

Article in BMC bioinformatics, 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

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

9 authors.

Stefan PastoreInstitute for Human Genetics, University Medical Center Johannes Gutenberg University, 55131, Mainz, Germany.
Philipp HillenbrandInstitute of Physiological Chemistry, University Medical Center Johannes Gutenberg University, 55128, Mainz, Germany.
Nils MolnarInstitute for Human Genetics, University Medical Center Johannes Gutenberg University, 55131, Mainz, Germany.
Irina KovlyaginaInstitute of Physiological Chemistry, University Medical Center Johannes Gutenberg University, 55128, Mainz, Germany.
Monika Chanu ChongthamLeibniz Institute for Resilience Research, 55122, Mainz, Germany.
Stanislav SysInstitute for Human Genetics, University Medical Center Johannes Gutenberg University, 55131, Mainz, Germany.
Beat LutzInstitute of Physiological Chemistry, University Medical Center Johannes Gutenberg University, 55128, Mainz, Germany.
Margarita Tevosian *Institute of Physiological Chemistry, University Medical Center Johannes Gutenberg University, 55128, Mainz, Germany. mtevosian@uni-mainz.de.
Susanne Gerber *Institute for Human Genetics, University Medical Center Johannes Gutenberg University, 55131, Mainz, Germany. sugerber@uni-mainz.de.

Funding

Deutsche Forschungsgemeinschaft INST247_1013-1 FUGG
6 · The paper itself

Abstract

backgroundTissue clearing combined with light-sheet microscopy is gaining popularity among neuroscientists interested in unbiased assessment of their samples in 3D volume. However, the analysis of such data remains a challenge. ClearMap and CellFinder are tools for analyzing neuronal activity maps in an intact volume of cleared mouse brains. However, these tools lack a user interface, restricting accessibility primarily to scientists proficient in advanced Python programming. The application presented here aims to bridge this gap and make data analysis accessible to a wider scientific community.

resultsWe developed an easy-to-adopt graphical user interface for cell quantification and group analysis of whole cleared adult mouse brains. Fundamental statistical analysis, such as PCA and box plots, and additional visualization features allow for quick data evaluation and quality checks. Furthermore, we present a use case of ClearFinder GUI for cross-analyzing the same samples with two cell counting tools, highlighting the discrepancies in cell detection efficiency between them.

conclusionsOur easily accessible tool allows more researchers to implement the methodology, troubleshoot arising issues, and develop quality checks, benchmarking, and standardized analysis pipelines for cell detection and region annotation in whole volumes of cleared brains.

Indexed as

BrainSoftwareAnimalsImaging, Three-DimensionalMiceNeuronsUser-Computer Interface3D volumetric imagingAtlas alignmentCell countTissue clearing

Identifiers

PMID39838291
PMCPMC11753021

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LicenceCC BY
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Registered trials

None linked

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.