ArticleComputational and structural biotechnology journal2021
PySTACHIO: Python Single-molecule TrAcking stoiCHiometry Intensity and simulatiOn, a flexible, extensible, beginner-friendly and optimized program for analysis of single-molecule microscopy data.
Article in Computational and structural biotechnology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 23 citations in OpenAlex.
- Lipopolysaccharide clustering in colistin persistent and resistant bacteria.npj antimicrobials and resistance · 2025Article
- SlimVar for rapid in vivo single-molecule tracking of chromatin regulators in plants.Nature communications · 2025Article
- Aggresomes protect mRNA under stress in Escherichia coli.Nature microbiology · 2025Article
- iPAR: a new reporter for eukaryotic cytoplasmic protein aggregation.BMC methods · 2025Article
- FluoroTensor: Identification and tracking of colocalised molecules and their stoichiometries in multi-colour single molecule imaging via deep learning.Computational and structural biotechnology journal · 2024Article
- Correlating fluorescence microscopy, optical and magnetic tweezers to study single chiral biopolymers such as DNA.Nature communications · 2024Article
- Correlating viscosity and molecular crowding with fluorescent nanobeads and molecular probes:Interface focus · 2022Article
- MPTHub: An Open-Source Software for Characterizing the Transport of Particles in Biorelevant Media.Nanomaterials (Basel, Switzerland) · 2022Article
- Investigating molecular crowding during cell division and hyperosmotic stress in budding yeast with FRET.Current topics in membranes · 2021Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As camera pixel arrays have grown larger and faster, and optical microscopy techniques ever more refined, there has been an explosion in the quantity of data acquired during routine light microscopy. At the single-molecule level, analysis involves multiple steps and can rapidly become computationally expensive, in some cases intractable on office workstations. Complex bespoke software can present high activation barriers to entry for new users. Here, we redevelop our quantitative single-molecule analysis routines into an optimized and extensible Python program, with GUI and command-line implementations to facilitate use on local machines and remote clusters, by beginners and advanced users alike. We demonstrate that its performance is on par with previous MATLAB implementations but runs an order of magnitude faster. We tested it against challenge data and demonstrate its performance is comparable to state-of-the-art analysis platforms. We show the code can extract fluorescence intensity values for single reporter dye molecules and, using these, estimate molecular stoichiometries and cellular copy numbers of fluorescently-labeled biomolecules. It can evaluate 2D diffusion coefficients for the characteristically short single-particle tracking data. To facilitate benchmarking we include data simulation routines to compare different analysis programs. Finally, we show that it works with 2-color data and enables colocalization analysis based on overlap integration, to infer interactions between differently labelled biomolecules. By making this freely available we aim to make complex light microscopy single-molecule analysis more democratized.
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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.