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celltrackR (version 1.2.1)

Motion Trajectory Analysis

Description

Methods for analyzing (cell) motion in two or three dimensions. Available measures include displacement, confinement ratio, autocorrelation, straightness, turning angle, and fractal dimension. Measures can be applied to entire tracks, steps, or subtracks with varying length. While the methodology has been developed for cell trajectory analysis, it is applicable to anything that moves including animals, people, or vehicles. Some of the methodology implemented in this packages was described by: Beauchemin, Dixit, and Perelson (2007) , Beltman, Maree, and de Boer (2009) , Gneiting and Schlather (2004) , Mokhtari, Mech, Zitzmann, Hasenberg, Gunzer, and Figge (2013) , Moreau, Lemaitre, Terriac, Azar, Piel, Lennon-Dumenil, and Bousso (2012) , Textor, Peixoto, Henrickson, Sinn, von Andrian, and Westermann (2011) , Textor, Sinn, and de Boer (2013) , Textor, Henrickson, Mandl, von Andrian, Westermann, de Boer, and Beltman (2014) .

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Version

Install

install.packages('celltrackR')

Monthly Downloads

296

Version

1.2.1

License

GPL-2

Maintainer

Johannes Textor

Last Published

August 26th, 2024

Functions in celltrackR (1.2.1)

beaucheminTrack

Simulate a 3D Cell Track Using the Beauchemin Model

as.tracks.data.frame

Convert from Data Frame to Tracks

Compute a Measure on a Track in a Staggered Fashion

Angle between Two Steps

Convert from Tracks to List

Angle with a Reference Plane

as.data.frame.tracks

Convert Tracks to Data Frame

Simulate Tracks via Bootstrapping of Speed and Turning Angle from a Real Track Dataset

Angle with a Reference Direction

Minimum Distance between Two Cells

Find Pairs of Tracks

Angle with a Reference Point

Bounding Box of a Tracks Object

distanceToPoint

Distance to a Reference Point

distanceToPlane

Distance to a Reference Plane

Simulate an Uncorrelated Random Walk

getFeatureMatrix

Obtaining A Feature Matrix

Test Unbiasedness of Motion

Distance between pairs of tracks at every timepoint

Plot Tracks in 2D

Open the package cheat sheet

normalizeToDuration

Normalize a Measure to Track Duration

celltrackR: Quantitative analysis of motion.

normalizeTracks

Normalize Tracks

interpolateTrack

Interpolate Track Positions

get.immap.metadata

Get Track Metadata from ImmuneMap

Distance between Two Steps

Plot Tracks in 3D

Length of Longest Track

Get Single Steps Starting at a Specific Time from a Subset of Tracks

plotTrackMeasures

Bivariate Scatterplot of Track Measures

Sort Track Positions by Time

Get Track Prefixes

read.tracks.csv

Read Tracks from Text File

Generate Tracks by Simulation

Find Pairs of Steps Occurring at the Same Time

Compute Time Step of Tracks

Find All Unique Time Points in a Track Dataset

projectDimensions

Extract Spatial Dimensions

Decompose Track(s) into Subtracks

subtracksByTime

Extract Subtracks Starting at a Specific Time

Process Tracks Containing Gaps

trackFeatureMap

Dimensionality Reduction on Track Features

Select Tracks by Measure Values

Split Track into Multiple Tracks

Staggered Version of a Function

Create Track Object from Single Track

Angle Between Two Vectors

Subsample Track by Constant Factor

analyzeStepPairs

Find Distances and Angles for all Pairs of Steps

Read tracks from ImmuneMap

Two-Photon Data: Neutrophils responding to an infection in the ear

analyzeCellPairs

Find Distances and Angles for all Pairs of Tracks

aggregate.tracks

Compute Summary Statistics of Subtracks

Angle between Two Tracks

Two-Photon Data: B Cells in a Lymph Node

Two-Photon Data: T Cells in a Lymph Node