Biological ImagingBioinformaticsPeer-reviewed journal article
Visualization & Quality Control Tools for Large-scale Multiplex Tissue Analysis in TissUUmaps 3
Andrea BeháňováiD, Christophe AveneliD, Axel AnderssoniD, Eduard ChelebianiD, Anna H. KlemmiD, Lina Wik LeissiD, Arne ÖstmaniD, Carolina WählbyiD
Abstract
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 e.g. 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.
- assay: spatial transcriptomics
- research focus: cell type annotation
- research focus: clustering
- research focus: cell-cell communication
- research focus: benchmarking
- approach: experimental assay
- Citations
- 7
- FWCI
- 0.73
- Field percentile
- top 38%
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