Welcome to saSPT’s documentation!
saspt is a Python tool for analyzing single particle tracking (SPT) experiments. It uses
state arrays, a kind of variational Bayesian framework that learns intelligible models
given raw trajectories from an SPT experiment.
There are a lot of great SPT analysis tools out there. We found it useful to
it is simple and flexible enough to accommodate a wide variety of underlying stochastic models;
its outputs are familiar
it imposes no prior beliefs on the number of dynamic states;
it uses tried-and-true Bayesian methods (marginalization over nuisance parameters) to deal with measurement error in a natural way.
I originally wrote
saspt to deal with live cell protein tracking experiments.
In the complex intracellular environment, a protein can occupy a large and unknown number of molecular
states with distinct dynamics.
saspt provides a simple way to measure the number,
characteristics, and fractional occupations of these states. It is also “smart” enough to deal with
situations where there may not be discrete states.
If you want to jump right into working with
saspt, see Quickstart. If you want a
more detailed explanation of why
saspt exists, see Background.
If you want to dig into the guts of the actual model and inference algorithm, see The state array model.
saspt stands for “state arrays for single particle tracking”.)
What does saSPT do?
saspt takes a set of trajectories from a tracking experiment, and identifies a mixture model to explain
them. It is designed to work natively with
What doesn’t saSPT do?
sasptdoesn’t do tracking; it takes trajectories as input. (See: Q. Does saspt provide a way to do tracking?)
sasptdoesn’t model transitions between states. For that purpose, we recommend the excellent vbSPT package.
sasptdoesn’t check the quality of the input data.
sasptexpects you to know the parameters for your imaging experiment, including pixel size, frame rate, and focal depth.
saspt only supports a small range of physical models. That may change as the package grows.
- The state array model
- Note on input format
- File reading
- Q. Does
sasptprovide a way to do tracking?
- Q. Why doesn’t
sasptsupport input format X?
- Q. Why are the default diffusion coefficients log-spaced?
- Q. How does
sasptestimate the posterior occupations, given the posterior distribution?
- Q. I want to measure the fraction of particles in a particular state. How do I do that?
- Q. What is defocalization?
- Q. Does