Visualization and quality control tools for large-scale multiplex tissue analysis in TissUUmaps3.

Cell classification quality control spatial omics visualization

Journal

Biological imaging
ISSN: 2633-903X
Titre abrégé: Biol Imaging
Pays: England
ID NLM: 9918284179906676

Informations de publication

Date de publication:
2023
Historique:
received: 08 11 2022
revised: 18 01 2023
accepted: 13 02 2023
medline: 15 3 2024
pubmed: 15 3 2024
entrez: 15 3 2024
Statut: epublish

Résumé

Large-scale multiplex tissue analysis aims to understand processes such as development and tumor formation by studying the occurrence and interaction of cells in local environments in, for example, tissue samples from patient cohorts. A typical procedure in the analysis is to delineate individual cells, classify them into cell types, and analyze their spatial relationships. All steps come with a number of challenges, and to address them and identify the bottlenecks of the analysis, it is necessary to include quality control tools in the analysis workflow. This makes it possible to optimize the steps and adjust settings in order to get better and more precise results. Additionally, the development of automated approaches for tissue analysis requires visual verification to reduce skepticism with regard to the accuracy of the results. Quality control tools could be used to build users' trust in automated approaches. In this paper, we present three plugins for visualization and quality control in large-scale multiplex tissue analysis of microscopy images. The first plugin focuses on the quality of cell staining, the second one was made for interactive evaluation and comparison of different cell classification results, and the third one serves for reviewing interactions of different cell types.

Identifiants

pubmed: 38487686
doi: 10.1017/S2633903X23000053
pii: S2633903X23000053
pmc: PMC10936381
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e6

Informations de copyright

© The Author(s) 2023.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Auteurs

Andrea Behanova (A)

Department of Information Technology and SciLifeLab BioImage Informatics Facility, Uppsala University, Uppsala, Sweden.

Christophe Avenel (C)

Department of Information Technology and SciLifeLab BioImage Informatics Facility, Uppsala University, Uppsala, Sweden.

Axel Andersson (A)

Department of Information Technology and SciLifeLab BioImage Informatics Facility, Uppsala University, Uppsala, Sweden.

Eduard Chelebian (E)

Department of Information Technology and SciLifeLab BioImage Informatics Facility, Uppsala University, Uppsala, Sweden.

Anna Klemm (A)

Department of Information Technology and SciLifeLab BioImage Informatics Facility, Uppsala University, Uppsala, Sweden.

Lina Wik (L)

Department of Oncology-Pathology, Karolinska Institutet, Solna, Sweden.

Arne Östman (A)

Department of Oncology-Pathology, Karolinska Institutet, Solna, Sweden.

Carolina Wählby (C)

Department of Information Technology and SciLifeLab BioImage Informatics Facility, Uppsala University, Uppsala, Sweden.

Classifications MeSH