ArticleBioinformatics (Oxford, England)2022
Stitching and registering highly multiplexed whole-slide images of tissues and tumors using ASHLAR.
Article in Bioinformatics (Oxford, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 82 papers, 1 of them a synthesis that pooled it.
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Who cites it
82 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- RNF43 p.G659fs leads to natural killer cell dysfunction in MSI-high colorectal cancer through PI3K/AKT/mTOR signaling and HLA-E up-regulation.Science advances · 2026Article
- HIGH-DIMENSIONAL MULTI-OMIC MAPPING OF POST-MORTEM HUMAN BRAIN USING ITERATIVE INDIRECT IMMUNOFLUORESCENCE IMAGING ON XENIUM-PROCESSED TISSUES.bioRxiv : the preprint server for biology · 2026Article
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- Uncovering the signaling networks of disseminated glioblastoma cells in vivo with INSIGHT.Nature communications · 2026Article
- Evidence of endothelial anergy and T-cell exclusion in microsatellite stable colorectal liver metastases revealed through human hemi-liver perfusion and spatial transcriptomics.Molecular cancer · 2026Article
- Cyclic immunofluorescence platform using photocleavable linkers for direct antibody labeling enables cancer phenotyping.bioRxiv : the preprint server for biology · 2026Article
- Image-based, pooled phenotyping reveals multidimensional, disease-specific variant effects.Cell · 2026Article
- Clinical responses to trastuzumab deruxtecan in molecularly defined ependymoma.NPJ precision oncology · 2026Article
- Modeling development of tertiary lymphoid structures in pulmonary tuberculosis by 3D profiling and trajectory analysis.bioRxiv : the preprint server for biology · 2026Article
- Longitudinal spatial neutrophil profiling during ACT in murine melanoma reveals distinct lymph node infiltration patterns.NPJ systems biology and applications · 2026Article
- SPOmiAlign: a modality-agnostic computational framework for multimodal spatial omics alignment enabled by a feature matching foundation model.Briefings in bioinformatics · 2026Article
- MIAAIM: Multi-omics image integration with dimensional reduction for tissue state mapping.PLoS computational biology · 2026Article
- Ex Vivo Immuno-Oncology Platform Reveals Spatial T-cell Infiltration Patterns Linked to ATR Inhibition Responses in High-Grade Serous Ovarian Cancer.Cancer immunology research · 2026Article
- Quantifying the Efficacy of Deep Learning-Driven Deformable Registration in Multiplexed-Immunofluorescence Imaging for Nucleus Subtype Classification.The journal of machine learning for biomedical imaging · 2026Article
- STARCall integrates image stitching, alignment, and read calling to enable scalable analysis of in situ sequencing data.PLoS computational biology · 2026Article
22 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors.
Funding
Abstract
motivationStitching microscope images into a mosaic is an essential step in the analysis and visualization of large biological specimens, particularly human and animal tissues. Recent approaches to highly multiplexed imaging generate high-plex data from sequential rounds of lower-plex imaging. These multiplexed imaging methods promise to yield precise molecular single-cell data and information on cellular neighborhoods and tissue architecture. However, attaining mosaic images with single-cell accuracy requires robust image stitching and image registration capabilities that are not met by existing methods.
resultsWe describe the development and testing of ASHLAR, a Python tool for coordinated stitching and registration of 103 or more individual multiplexed images to generate accurate whole-slide mosaics. ASHLAR reads image formats from most commercial microscopes and slide scanners, and we show that it performs better than existing open-source and commercial software. ASHLAR outputs standard OME-TIFF images that are ready for analysis by other open-source tools and recently developed image analysis pipelines. AVAILABILITY AND IMPLEMENTATION: ASHLAR is written in Python and is available under the MIT license at https://github.com/labsyspharm/ashlar. The newly published data underlying this article are available in Sage Synapse at https://dx.doi.org/10.7303/syn25826362; the availability of other previously published data re-analyzed in this article is described in Supplementary Table S4. An informational website with user guides and test data is available at https://labsyspharm.github.io/ashlar/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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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.