Package: celltrackR 1.2.1

celltrackR: Motion Trajectory Analysis

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) <doi:10.4049/jimmunol.178.9.5505>, Beltman, Maree, and de Boer (2009) <doi:10.1038/nri2638>, Gneiting and Schlather (2004) <doi:10.1137/S0036144501394387>, Mokhtari, Mech, Zitzmann, Hasenberg, Gunzer, and Figge (2013) <doi:10.1371/journal.pone.0080808>, Moreau, Lemaitre, Terriac, Azar, Piel, Lennon-Dumenil, and Bousso (2012) <doi:10.1016/j.immuni.2012.05.014>, Textor, Peixoto, Henrickson, Sinn, von Andrian, and Westermann (2011) <doi:10.1073/pnas.1102288108>, Textor, Sinn, and de Boer (2013) <doi:10.1186/1471-2105-14-S6-S10>, Textor, Henrickson, Mandl, von Andrian, Westermann, de Boer, and Beltman (2014) <doi:10.1371/journal.pcbi.1003752>.

Authors:Johannes Textor [aut, cre], Katharina Dannenberg [aut], Jeffrey Berry [aut], Gerhard Burger [aut], Annie Liu [aut], Mark Miller [aut], Inge Wortel [aut]

celltrackR_1.2.1.tar.gz
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celltrackR.pdf |celltrackR.html
celltrackR/json (API)
NEWS

# Install 'celltrackR' in R:
install.packages('celltrackR', repos = c('https://jtextor.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • BCells - Two-Photon Data: B Cells in a Lymph Node
  • Neutrophils - Two-Photon Data: Neutrophils responding to an infection in the ear
  • TCells - Two-Photon Data: T Cells in a Lymph Node

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.08 score 4 scripts 303 downloads 71 exports 2 dependencies

Last updated 3 months agofrom:68fd4b56f8. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 26 2024
R-4.5-winOKOct 26 2024
R-4.5-linuxOKOct 26 2024
R-4.4-winOKOct 26 2024
R-4.4-macOKOct 26 2024
R-4.3-winOKOct 26 2024
R-4.3-macOKOct 26 2024

Exports:analyzeCellPairsanalyzeStepPairsangleCellsangleStepsangleToDirangleToPlaneangleToPointapplyStaggeredas.tracksasphericitybeaucheminTrackbootstrapTrackboundingBoxbrownianTrackcellPairscheatsheetclusterTracksdisplacementdisplacementRatiodisplacementVectordistanceCellsdistanceStepsdistanceToPlanedistanceToPointdurationfilterTracksfractalDimensionget.immap.metadataget.immap.tracksgetFeatureMatrixhotellingsTesthurstExponentinterpolateTrackis.tracksmaxDisplacementmaxTrackLengthmeanTurningAnglenormalizeToDurationnormalizeTracksoutreachRatiooverallAngleoverallDotoverallNormDotpairsByTimeparse.immap.jsonplot3dplotTrackMeasuresprefixesprojectDimensionsread.immap.jsonread.tracks.csvrepairGapsselectStepsselectTrackssimulateTracksspeedsplitTracksquareDisplacementstaggeredstepPairsstraightnesssubsamplesubtrackssubtracksByTimetimePointstimeSteptrackFeatureMaptrackLengthtracksvecAnglewrapTrack

Dependencies:ellipsepracma

Clustering Tracks with CelltrackR

Rendered fromclustering.Rmdusingknitr::rmarkdownon Oct 26 2024.

Last update: 2024-03-27
Started: 2020-03-31

Quality Control and Preprocessing

Rendered fromQC.Rmdusingknitr::rmarkdownon Oct 26 2024.

Last update: 2022-03-21
Started: 2020-03-31

Quality Control and Preprocessing of the Datasets in the Package

Rendered fromdata-QC.Rmdusingknitr::rmarkdownon Oct 26 2024.

Last update: 2022-03-21
Started: 2022-03-21

Reading, Converting, and Filtering Tracking Data

Rendered fromreading-converting-data.Rmdusingknitr::rmarkdownon Oct 26 2024.

Last update: 2022-03-21
Started: 2020-03-31

Simulating Tracks

Rendered fromsimulation.Rmdusingknitr::rmarkdownon Oct 26 2024.

Last update: 2022-03-21
Started: 2020-03-31

Track Analysis Methods

Rendered fromana-methods.Rmdusingknitr::rmarkdownon Oct 26 2024.

Last update: 2022-03-21
Started: 2020-03-31

Readme and manuals

Help Manual

Help pageTopics
Compute Summary Statistics of Subtracksaggregate aggregate.tracks
Find Distances and Angles for all Pairs of TracksanalyzeCellPairs
Find Distances and Angles for all Pairs of StepsanalyzeStepPairs
Angle AnalysisAngleAnalysis
Angle between Two TracksangleCells
Angle between Two StepsangleSteps
Angle with a Reference DirectionangleToDir
Angle with a Reference PlaneangleToPlane
Angle with a Reference PointangleToPoint
Compute a Measure on a Track in a Staggered FashionapplyStaggered
Convert Tracks to Data Frameas.data.frame.tracks
Convert from Tracks to Listas.list.tracks
Convert from Data Frame to Tracksas.tracks.data.frame
Two-Photon Data: B Cells in a Lymph NodeBCells
Simulate a 3D Cell Track Using the Beauchemin ModelbeaucheminTrack
Simulate Tracks via Bootstrapping of Speed and Turning Angle from a Real Track DatasetbootstrapTrack
Bounding Box of a Tracks ObjectboundingBox
Simulate an Uncorrelated Random WalkbrownianTrack
Find Pairs of TrackscellPairs
Open the package cheat sheetcheatsheet
Cluster TracksclusterTracks
Minimum Distance between Two CellsdistanceCells
Distance between Two StepsdistanceSteps
Distance to a Reference PlanedistanceToPlane
Distance to a Reference PointdistanceToPoint
Filter TracksfilterTracks
Get Track Metadata from ImmuneMapget.immap.metadata
Obtaining A Feature MatrixgetFeatureMatrix
Test Unbiasedness of MotionhotellingsTest
Interpolate Track PositionsinterpolateTrack
Length of Longest TrackmaxTrackLength
Two-Photon Data: Neutrophils responding to an infection in the earNeutrophils
Normalize a Measure to Track DurationnormalizeToDuration
Normalize TracksnormalizeTracks
Distance between pairs of tracks at every timepointpairsByTime
Plot Tracks in 2Dplot.tracks
Plot Tracks in 3Dplot3d
Bivariate Scatterplot of Track MeasuresplotTrackMeasures
Get Track Prefixesprefixes
Extract Spatial DimensionsprojectDimensions
Read Tracks from Text Fileread.tracks.csv
Read tracks from ImmuneMapget.immap.tracks parse.immap.json read.immap.json ReadImmuneMap
Process Tracks Containing GapsrepairGaps
Get Single Steps Starting at a Specific Time from a Subset of TracksselectSteps
Select Tracks by Measure ValuesselectTracks
Generate Tracks by SimulationsimulateTracks
Sort Track Positions by Timesort.tracks
Split Track into Multiple TrackssplitTrack
Staggered Version of a Functionstaggered
Find Pairs of Steps Occurring at the Same TimestepPairs
Subsample Track by Constant Factorsubsample
Decompose Track(s) into Subtrackssubtracks
Extract Subtracks Starting at a Specific TimesubtracksByTime
Two-Photon Data: T Cells in a Lymph NodeTCells
Find All Unique Time Points in a Track DatasettimePoints
Compute Time Step of TrackstimeStep
Dimensionality Reduction on Track FeaturestrackFeatureMap
Track Measuresasphericity displacement displacementRatio displacementVector duration fractalDimension hurstExponent maxDisplacement meanTurningAngle outreachRatio overallAngle overallDot overallNormDot speed squareDisplacement straightness trackLength TrackMeasures
Tracks Objectsas.tracks as.tracks.list c.tracks is.tracks tracks
Angle Between Two VectorsvecAngle
Create Track Object from Single TrackwrapTrack