PySTACHIO: Python Single-molecule TrAcking stoiCHiometry Intensity and simulatiOn, a flexible, extensible, beginner-friendly and optimized program for analysis of single-molecule microscopy
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 microcopy. 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.
Code (0)
등록된 구현이 없습니다.
Tasks
Art AnalysisBenchmarkingMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Single molecule narrowfield microscopy of protein-DNA binding dynamics in glucose signal transduction of live yeast cells
Single-molecule narrowfield microscopy is a versatile tool to investigate a diverse range of protein dynamics in live cells and has been extensively used in bacteria. Here, we describe how these methods can be extended t…
A graph representation of molecular ensembles for polymer property prediction
Synthetic polymers are versatile and widely used materials. Similar to small organic molecules, a large chemical space of such materials is hypothetically accessible. Computational property prediction and virtual screeni…
BIG-bench Machine LearningGraph Neural NetworkProperty PredictionSingle-molecular quantification of flowering control proteins within nuclear condensates in live whole Arabidopsis root
Here we describe the coupled standardisation of two complementary fluorescence imaging techniques and apply it to liquid-liquid phase separated condensates formed from an EGFP fluorescent reporter of Flowering Control Lo…
Analytical tools for single-molecule fluorescence imaging in cellulo
Recent technological advances in cutting-edge ultrasensitive fluorescence microscopy have allowed single-molecule imaging experiments in living cells across all three domains of life to become commonplace. Single-molecul…
Probing DNA interactions with proteins using a single-molecule toolbox: inside the cell, in a test tube, and in a computer
DNA-interacting proteins have roles multiple processes, many operating as molecular machines which undergo dynamic metastable transitions to bring about their biological function. To fully understand this molecular heter…