ArticleBioinformatics (Oxford, England)2022
Scalable analysis of whole slide spatial proteomics with Harpy.
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 3 papers.
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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.
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Who cites it
3 citing papers in PubMed.
- Do papers tell the whole story? A benchmark and framework for uncovering hidden implementation gaps in bioinformatics.Briefings in bioinformatics · 2026Article
- OpenIMC: an open-source platform for analyzing single-cell and spatial proteomics by imaging mass cytometry.BMC bioinformatics · 2026Article
- OpenIMC: an open-source platform for analyzing single-cell and spatial proteomics by imaging mass cytometry.Research square · 2026Article
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Authors and funding
8 authors.
Funding
Abstract
motivationCurrent spatial proteomics data analysis workflows are limited in efficiency and scalability when applied to gigapixel sized datasets. Moreover, they often lack extensive quality control tools and exhibit limited interoperability with existing spatial omics analysis ecosystems.
resultsWe introduce Harpy, a new Python workflow capable of accelerated processing of large spatial proteomics datasets. We demonstrate the utility of Harpy on four datasets and show that it can rapidly apply state-of-the-art segmentation and feature extraction via parallel processing. Each analysis step is accompanied by appropriate quality control steps. Scalable clustering of cells and pixels allows identification of cell types, processed up to 27 times faster than previously reported. Processing and visualization can be performed locally or on high-performance computing servers. Additionally, Harpy integrates well with existing spatial single-cell analysis tools in the Python and R software ecosystem. AVAILABILITY AND IMPLEMENTATION: Harpy is available on GitHub at https://github.com/saeyslab/harpy and archived on Zenodo at https://doi.org/10.5281/zenodo.15546703.
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Registered trials
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.