Unlock the full potential of your multiomic tissue analysis with our powerful spatial software solutions. Designed for speed and getting fast results, our data analysis tools enable researchers to visualize, quantify, and interpret complex spatial biology data with confidence and speed.
Revolutionizing How You Manage Spatial Data
At the core of our software ecosystem is Quantitative Pathology TIFF (QPTIFF), which is a specialized image file format designed to make spatial imaging practical and efficient. It compresses massive, multichannel, high-quality images into gigabyte-sized files instead of terabytes that dramatically reduces storage demands and accelerates data analysis workflows without compromising image quality.
This technology integrates seamlessly with proprietary software, partner platforms, and open-source tools. QPTIFF supports multi-modal data, including DNA, RNA, and protein.
Essential Elements for Deep Spatial Insights
Algorithms compress terabyte-sized images into gigabyte-sized QPTIFFs without compromising quality.
Cell segmentation is vital to spatial biology, allowing precise cell quantification, spatial analysis, and insight into complex systems and disease research.
Clustering and phenotyping identify cell populations, revealing spatial, and functional patterns linked to disease. These insights drive breakthroughs in understanding biological systems and enable targeted therapy development.
Leverage cellular neighborhood mapping to uncover how cells interact within their microenvironment to reveal critical biological relationships and disease mechanisms.
Spatial signatures are crucial for translational and clinical research, connecting tissue-specific patterns with therapeutic understanding and precision therapeutics, bridging molecular analysis with clinical applications.
PhenoCycler-Fusion software
Perform spatial analysis across entire tissue sections for comprehensive spatial insights.
Separate weak and overlapping fluorescent signals from background autofluorescence for accurate quantification.
Reliably identify individual cells in dense, heterogeneous tissue environments.
Analyze hundreds of images in minutes, accelerating discovery timelines.
Render immunofluorescence images as simulated H&E or DAB for intuitive interpretation.
A suite of software solutions for the PhenoImager HT 2.0
The PhenoImager HT 2.0 software suite streamlines workflows, enhances data quality, and provides powerful capabilities for visualization, segmentation, and spatial mapping.
PhenoImager HT 2.0: High-throughput Spatial Imaging
The PhenoImager HT delivers unmatched speed and scalability for spatial biology. Combined with our software solutions, the PhenoImager HT enables efficient processing of complex tissue datasets, cellular phenotyping, and spatial signature development—accelerating biomarker discovery and translational research.
Phenochart: Visualize and Annotate Spatial Images
Phenochart enables viewing and annotating digital slides. With integrated spectral unmixing, researchers can open raw image files, mark regions of interest, and export annotations for downstream analysis in inForm.
inForm: Automated Tissue Analysis for Multimarker Studies
inForm delivers advanced image processing and tissue segmentation for comparative studies involving multiple markers and specimens. Patented algorithms handle spectral unmixing and image stitching, preparing data for analysis across a variety of compatible tools to improve reproducibility.
phenoptr & phenoptrReports: Spatial Relationships Made Actionable
phenoptrReports provides intuitive tools for analyzing spatial relationships among cellular phenotypes. Visualize co-expression patterns, assess unmixing quality, and generate shareable reports that make complex spatial data easy to interpret and communicate.
Our software ecosystem extends beyond proprietary solutions to include trusted partners who deliver specialized tools for spatial biology. These providers offer advanced capabilities from image management and computational pathology to AI-powered analysis and cloud-based platforms. By integrating with our instruments and data formats, these solutions help researchers accelerate discovery, streamline analysis, and unlock deeper biological insights.
VisioPharm develops scalable software solutions for scientists and pathologists engaged in tissue-based research and diagnostics. Their Oncotopix Augmented Pathology™ solution fits the needs and volumes of both research and diagnostic labs.
Enable Medicine accelerates insight discovery by generating, managing, and analyzing spatial biology data on the Enable Cloud Platform. The platform hosts an image processing and analytics suite, a cloud database for indexing biological data into searchable maps, and a lab for generating spatial biology data.
OracleBio is a global leader in quantitative digital pathology providing image analysis services to pharma and biotech clients worldwide. Leveraging cutting-edge technology, such as AI Deep Learning and cloud computing, they deliver robust data packages within a quality management framework to support preclinical, translational and clinical research.
Indica Labs is the world’s leading provider of computational pathology software and image analysis services. Their flagship HALO® and HALO AI platform facilitates quantitative evaluation of digital pathology images while HALO Link and HALO AP® provide collaborative image management for research and clinical workflows, respectively.
PathAI is a leading provider of AI-powered research tools and services for pathology. PathAI’s platform promises substantial improvements to the accuracy of diagnosis and the efficacy of treatment of diseases like cancer, leveraging modern approaches in machine and deep learning.
Open-source software solutions
QuPath is open-source software for bioimage analysis and is often used for digital pathology applications that offer a powerful set of tools for working with whole slide images.