Package 'flowcatchR' reference manual

Title:	Tools to analyze in vivo microscopy imaging data focused on tracking flowing blood cells
Description:	flowcatchR is a set of tools to analyze in vivo microscopy imaging data, focused on tracking flowing blood cells. It guides the steps from segmentation to calculation of features, filtering out particles not of interest, providing also a set of utilities to help checking the quality of the performed operations (e.g. how good the segmentation was). It allows investigating the issue of tracking flowing cells such as in blood vessels, to categorize the particles in flowing, rolling and adherent. This classification is applied in the study of phenomena such as hemostasis and study of thrombosis development. Moreover, flowcatchR presents an integrated workflow solution, based on the integration with a Shiny App and Jupyter notebooks, which is delivered alongside the package, and can enable fully reproducible bioimage analysis in the R environment.
Authors:	Federico Marini [aut, cre]
Maintainer:	Federico Marini <[email protected]>
License:	BSD_3_clause + file LICENSE
Version:	1.39.0
Built:	2024-07-01 04:16:31 UTC
Source:	https://github.com/bioc/flowcatchR

Add object contours to a `Frames` object Creates a `Frames` object containing raw information, combined with the segmented images and the relative trajectory under analysis

Description

If a TrajectorySet is provided and mode is set to trajectories, returns a Frames with all trajectories included in the IDs vector painted accordingly. If the mode is set to particles, it will just plot the particles (all) on all frames. If no TrajectorySet is provided, it will be computed with default parameters. If no binary.frames is provided, it will be computed also with default parameters

Usage

add.contours(
  raw.frames,
  binary.frames = NULL,
  trajectoryset = NULL,
  trajIDs = NULL,
  mode = "particles",
  col = NULL,
  channel = NULL
)
add.contours(
  raw.frames,
  binary.frames = NULL,
  trajectoryset = NULL,
  trajIDs = NULL,
  mode = "particles",
  col = NULL,
  channel = NULL
)

Arguments

`raw.frames`	A `Frames` object with raw images
`binary.frames`	A `Frames` object with preprocessed frames
`trajectoryset`	A `TrajectorySet` object
`trajIDs`	Numeric vector, the ID(s) of the trajectory.
`mode`	A character string, can assume the values `particles` or `trajectories`. Defaults to `particles`
`col`	A vector of color strings
`channel`	A character string, to select which channel to process

Value

A new Frames object with contours of the objects added

Author(s)

Federico Marini, [email protected], 2014

Examples

data("MesenteriumSubset")
## Not run: 
paintedTrajectories <- add.contours(raw.frames = MesenteriumSubset, 
                                    mode = "trajectories",channel="red")
paintedParticles <- add.contours(raw.frames = MesenteriumSubset, 
                                 mode = "particles",channel="red")
inspect.Frames(paintedTrajectories)
inspect.Frames(paintedParticles)

## End(Not run)

data("MesenteriumSubset")
## Not run: 
paintedTrajectories <- add.contours(raw.frames = MesenteriumSubset, 
                                    mode = "trajectories",channel="red")
paintedParticles <- add.contours(raw.frames = MesenteriumSubset, 
                                 mode = "particles",channel="red")
inspect.Frames(paintedTrajectories)
inspect.Frames(paintedParticles)

## End(Not run)

Combines the information from a raw `Frames` object and the corresponding preprocessed one

Description

All objects are painted with a unique colour - for sake of speed

Usage

addParticles(raw.frames, binary.frames, col = NULL)
addParticles(raw.frames, binary.frames, col = NULL)

Arguments

`raw.frames`	A `Frames` object containing the raw images
`binary.frames`	A `Frames` object with the preprocessed versions of the images (e.g. segmented)
`col`	A color character string, to select which color will be used for drawing the contours of the particles. If not specified, it will default according to the objects provided

Value

A Frames object, whose images are the combination of the raw images with the segmented objects drawn on them

Author(s)

Federico Marini, [email protected], 2014

Info on the dimensions of the FOV

Description

Auxiliary function to return the dimensions of the field of interest

Usage

axesInfo(frames)
axesInfo(frames)

Arguments

frames

A Frames object

Value

A list object, containing the extremes of the field of interest (x-y-z, where z is time)

Author(s)

Federico Marini, [email protected], 2014

A sample `ParticleSet` object

Description

The sample ParticleSet object is constituted by the platelets identified from the MesenteriumSubset data

Author(s)

Federico Marini, [email protected], 2014

Channel extraction for `objects`

Description

channel

Usage

channel.Frames(frames, mode)
channel.Frames(frames, mode)

Arguments

`frames`	A `Frames` object
`mode`	A character value specifying the target mode for conversion.

Value

A Frames object with just the infotmation on the selected channel

Examples

data("MesenteriumSubset")
channel.Frames(MesenteriumSubset,"red")
data("MesenteriumSubset")
channel.Frames(MesenteriumSubset,"red")

Calculates the Mean Squared Displacement for a trajectory

Description

Calculates the Mean Squared Displacement for a trajectory

Usage

computeMSD(sx, sy, until = 4)
computeMSD(sx, sy, until = 4)

Arguments

`sx`	x axis positions along the trajectory
`sy`	y axis positions along the trajectory
`until`	how many points should be included in the Mean Squared Displacement curve

Value

A numeric vector containing the values of the MSD

Author(s)

Federico Marini, [email protected], 2014

Cut borders of a `Frames` object

Description

Performs cropping on the Frames object, selecting how many pixels should be cut on each side

Usage

crop.Frames(
  frames,
  cutLeft = 5,
  cutRight = 5,
  cutUp = 5,
  cutDown = 5,
  cutAll = 0,
  testing = FALSE,
  ...
)
crop.Frames(
  frames,
  cutLeft = 5,
  cutRight = 5,
  cutUp = 5,
  cutDown = 5,
  cutAll = 0,
  testing = FALSE,
  ...
)

Arguments

`frames`	An input `Frames` object
`cutLeft`	Amount of pixels to be cut at the side
`cutRight`	Amount of pixels to be cut at the side
`cutUp`	Amount of pixels to be cut at the side
`cutDown`	Amount of pixels to be cut at the side
`cutAll`	Amount of pixels to be cut at all sides. Overrides the single side values
`testing`	Logical, whether to just test the cropping or to actually perform it. Default set to `FALSE`
`...`	Arguments to be passed to `display` (e.g. setting the `method` argument)

Details

Cropping can be performed with careful choice of all cutting sides, or cropping a single value from all sides

Value

A Frames object, with cropped frames in the image slot

Author(s)

Federico Marini, [email protected], 2014

Examples

data("MesenteriumSubset")
crop.Frames(MesenteriumSubset)

data("MesenteriumSubset")
crop.Frames(MesenteriumSubset)

Exports a `Frames` object

Description

Writes the images contained in the image slot of the Frames object elements. The images can be exported as single frames, or as a .gif image that is composed by the single frames.

Usage

export.Frames(
  frames,
  dir = tempdir(),
  nameStub = "testExport",
  createGif = FALSE,
  removeAfterCreatingGif = TRUE
)
export.Frames(
  frames,
  dir = tempdir(),
  nameStub = "testExport",
  createGif = FALSE,
  removeAfterCreatingGif = TRUE
)

Arguments

`frames`	A `Frames` object
`dir`	The path of the folder where the image should be written
`nameStub`	The stub for the file name, that will be used as a prefix for the exported images
`createGif`	Logical, whether to create or not an animated .gif file
`removeAfterCreatingGif`	Logical, whether to remove the single exported .png images after creating the single .gif

Value

Image files are written in the desired location

Author(s)

Federico Marini, [email protected], 2014

Examples

data("MesenteriumSubset")
## Not run: export.Frames(MesenteriumSubset,nameStub="subset_export_",
                       createGif=TRUE,removeAfterCreatingGif=FALSE)
## End(Not run)

data("MesenteriumSubset")
## Not run: export.Frames(MesenteriumSubset,nameStub="subset_export_",
                       createGif=TRUE,removeAfterCreatingGif=FALSE)
## End(Not run)

Exports a `ParticleSet` object

Description

Writes the particles contained in the particles data frame slot of the ParticleSet object elements. A track of the provenience of the particles is stored as a comment line above the header

Usage

export.particles(
  particleset,
  dir = tempdir(),
  nameStub = "testExport_particles"
)
export.particles(
  particleset,
  dir = tempdir(),
  nameStub = "testExport_particles"
)

Arguments

`particleset`	A `ParticleSet` object
`dir`	The path of the folder where the particle sets should be written
`nameStub`	The stub for the file name, that will be used as a prefix for the exported particle sets

Value

Particle sets files are written in the desired location

Author(s)

Federico Marini, [email protected], 2014

Examples

data("candidate.platelets")
## Not run: export.particles(candidate.platelets)

data("candidate.platelets")
## Not run: export.particles(candidate.platelets)

Calculate a set of kinematics parameters from a single trajectory

Description

Usage

extractKinematics.traj(
  trajectoryset,
  trajectoryID,
  acquisitionFrequency = 30,
  scala = 50
)
extractKinematics.traj(
  trajectoryset,
  trajectoryID,
  acquisitionFrequency = 30,
  scala = 50
)

Arguments

`trajectoryset`	A `TrajectorySet` object
`trajectoryID`	The ID of a single trajectory
`acquisitionFrequency`	The frame rate of acquisition for the images, in milliseconds
`scala`	The value of micro(?)meters to which each single pixel corresponds

Value

A KinematicsFeatures object

Author(s)

Federico Marini, [email protected], 2014

flowcatchR: analyzing time-lapse microscopy imaging, from detection to tracking

Description

A toolset to analyze in vivo microscopy imaging data focused on tracking flowing blood cells.

Details

flowcatchR is a set of tools to analyze in vivo microscopy imaging data, focused on tracking flowing blood cells. It guides the steps from segmentation to calculation of features, filtering out particles not of interest, providing also a set of utilities to help checking the quality of the performed operations (e.g. how good the segmentation was). The main novel contribution investigates the issue of tracking flowing cells such as in blood vessels, to categorize the particles in flowing, rolling and adherent. This classification is applied in the study of phenomena such as hemostasis and study of thrombosis development.

Author(s)

Federico Marini [email protected], Johanna Mazur [email protected], Harald Binder [email protected], 2015

Maintainer: Federico Marini [email protected]

Constructor for a `Frames` object

Description

Constructor for a Frames object

Usage

Frames(x, channel)
Frames(x, channel)

Arguments

`x`	A multi-dimensional `Image` object
`channel`	A character vector, can be 'red','green','blue' or 'all' (if in color mode)

Value

The created Frames object.

Author(s)

Federico Marini, [email protected], 2014

Examples

data("MesenteriumSubset")
inputImg <- Image(MesenteriumSubset)
Frames(inputImg,"red")

data("MesenteriumSubset")
inputImg <- Image(MesenteriumSubset)
Frames(inputImg,"red")

Frames class

Description

S4 class for storing information on multiple images belonging to the same time-lapse experiment. It is designed as a subclass of the existing Image class from the EBImage package

Slots

channel: A character vector, can be 'red','green','blue' or 'all' (if in color mode)

Initialize a `ParticleSet` object for subsequent linking/tracking

Description

Initialize a ParticleSet object for subsequent linking/tracking

Usage

initialize.LinkedParticleSet(particleset, linkrange = 1)
initialize.LinkedParticleSet(particleset, linkrange = 1)

Arguments

`particleset`	A `ParticleSet` object
`linkrange`	The number of frames to look for candidate particles potentially belonging to the same track

Value

A ParticleSet object with slots dedicated for the tracking pre-filled

Author(s)

Federico Marini, [email protected], 2014

Explore the frames of a `Frames`

Description

The first frames of a Frames are displayed in the browser, and are interactively navigable.

Usage

inspect.Frames(
  frames,
  nframes = NULL,
  display.method = "browser",
  verbose = FALSE
)
inspect.Frames(
  frames,
  nframes = NULL,
  display.method = "browser",
  verbose = FALSE
)

Arguments

`frames`	A `Frames` object
`nframes`	The number of frames to display (default value: `NULL`, all are displayed )
`display.method`	Method for displaying, can be either `raster` or `browser`. Defaults to `browser`, by opening a window in the browser
`verbose`	Logical, whether to provide additional output on the command line alongside with the images themselves

Value

inspect.Frames returns an invisible NULL.

Author(s)

Federico Marini, [email protected], 2014

Examples

data("MesenteriumSubset")
## Not run: inspect.Frames(MesenteriumSubset)

data("MesenteriumSubset")
## Not run: inspect.Frames(MesenteriumSubset)

Calculate a set of kinematics parameter from a `TrajectorySet` object, or a single parameter, or from a single trajectory (all possible combinations)

Description

The computed set of parameters include delta.x, delta.t and delta.v (displacements and instantaneous velocity), totalTime, totalDistance, distStartToEnd, curvilinearVelocity, straightLineVelocity and linearityForwardProgression, Mean Squared Displacement, velocity autocorrelation, and more. If a single trajectory is specified, the computation is performed for that trajectory alone. If a parameter is specified, only that parameter is reported, either for one or all trajectories

Usage

kinematics(
  trajectoryset,
  trajectoryIDs = NULL,
  acquisitionFrequency = 30,
  scala = 50,
  feature = NULL
)
kinematics(
  trajectoryset,
  trajectoryIDs = NULL,
  acquisitionFrequency = 30,
  scala = 50,
  feature = NULL
)

Arguments

`trajectoryset`	A `TrajectorySet` object
`trajectoryIDs`	The ID of a single trajectory
`acquisitionFrequency`	The frame rate of acquisition for the images, in milliseconds
`scala`	The value of micro(?)meters to which each single pixel corresponds
`feature`	Character string, the name of the feature to be computed

Value

A KinematicsFeaturesSet object, or a KinematicsFeatures object, or an atomic value, or a list(eventually coerced to a vector)

Author(s)

Federico Marini, [email protected], 2014

Examples

data("candidate.platelets")
platelets.trajectories <- trajectories(candidate.platelets)
# for all trajectories, all features
alltrajs.features <- kinematics(platelets.trajectories)
# for one trajectory, all features
traj11features <- kinematics(platelets.trajectories,trajectoryIDs = 11)
# for all trajectories, one feature
alltrajs.curvVel <- kinematics(platelets.trajectories,feature = "curvilinearVelocity")
  
data("candidate.platelets")
platelets.trajectories <- trajectories(candidate.platelets)
# for all trajectories, all features
alltrajs.features <- kinematics(platelets.trajectories)
# for one trajectory, all features
traj11features <- kinematics(platelets.trajectories,trajectoryIDs = 11)
# for all trajectories, one feature
alltrajs.curvVel <- kinematics(platelets.trajectories,feature = "curvilinearVelocity")

KinematicsFeatures class

Description

S4 class for storing information on all kinematics features identified for a single trajectory

Slots

.Data: A list storing the information for the kinematics features

KinematicsFeaturesSet class

Description

S4 class for storing information on all kinematics features identified for all trajectories. Single KinematicsFeatures objects are the element of the main list

Slots

.Data: A list storing the information for the sets of kinematics features

Compute the length of render frames in a `Frames` object

Description

Compute the length of render frames in a Frames object

Usage

## S3 method for class 'Frames'
length(x)
## S3 method for class 'Frames'
length(x)

Arguments

`x`	A `Frames` object

Value

An integer number

Author(s)

Federico Marini, [email protected], 2014

Examples

data("MesenteriumSubset")
length(MesenteriumSubset)

data("MesenteriumSubset")
length(MesenteriumSubset)

Links a `ParticleSet` object

Description

Performs linking of the particles by tracking them through the frames

Usage

link.particles(
  particleset,
  L,
  R = 2,
  epsilon1 = 0.1,
  epsilon2 = 2,
  lambda1 = 1,
  lambda2 = 1,
  penaltyFunction = penaltyFunctionGenerator(),
  verboseOutput = FALSE,
  prog = FALSE,
  include.intensity = TRUE,
  include.area = FALSE
)
link.particles(
  particleset,
  L,
  R = 2,
  epsilon1 = 0.1,
  epsilon2 = 2,
  lambda1 = 1,
  lambda2 = 1,
  penaltyFunction = penaltyFunctionGenerator(),
  verboseOutput = FALSE,
  prog = FALSE,
  include.intensity = TRUE,
  include.area = FALSE
)

Arguments

`particleset`	A `ParticleSet` object
`L`	Maximum number of pixels an object can move in two consecutive frames
`R`	Linkrange, i.e. the number of consecutive frames to search for potential candidate links
`epsilon1`	A numeric value, to be used in the formula. Jitter for allowing angular displacements
`epsilon2`	A numeric value, to be used in the formula. Jitter for allowing spatial displacements
`lambda1`	A numeric value. Multiplicative factor for the penalty function
`lambda2`	A numeric value. Multiplicative factor applied to the angular displacement
`penaltyFunction`	A function structured in such a way to be applied as penalty function in the linking
`verboseOutput`	Logical, whether the output should report additional intermediate steps. For debugging use mainly
`prog`	Logical, whether the a progress bar should be shown during the tracking phase
`include.intensity`	Logical, whether to include also intensity change of the particles in the cost function calculation
`include.area`	Logical, whether to include also area change of the particles in the cost function calculation

Value

A LinkedParticleSet object

Author(s)

Federico Marini, [email protected], 2014

References

I F Sbalzarini and P Koumoutsakos."Feature point tracking and trajectory analysis for video imaging in cell biology." In: Journal of structural biology 151.2 (Aug. 2005), pp. 182-95. ISSN: 1047-8477. DOI: 10.1016/j.jsb.2005.06.002. URL: http://www.ncbi.nlm.nih.gov/pubmed/16043363

Examples

data("candidate.platelets")
tracked.platelets <- link.particles(candidate.platelets, L= 40)

data("candidate.platelets")
tracked.platelets <- link.particles(candidate.platelets, L= 40)

LinkedParticleSet class

Description

S4 class for storing information of particles after they have been tracked. It inherits the slots from the ParticleSet class.

Slots

tracking: A list storing all necessary information for the tracking algorithm to work, and for providing the information to the function to determine the trajectories

Match trajectories to related particles.

Description

Match trajectories to the related particles in the TrajectorySet and ParticleSet objects. This function returns a new ParticleSet object that contains as additional column the trajectory ID that the particular particle was assigned to. Used also by other routines, such as snap

Usage

matchTrajToParticles(particleset, trajectoryset)
matchTrajToParticles(particleset, trajectoryset)

Arguments

`particleset`	A `ParticleSet` object
`trajectoryset`	A `TrajectorySet` object coupled to the `particleset`

Value

A ParticleSet object with an additional column with the trajectory IDs

Author(s)

Federico Marini, [email protected], 2015

Examples

data(candidate.platelets)
trajs <- trajectories(candidate.platelets)
matchTrajToParticles(candidate.platelets, trajs)

data(candidate.platelets)
trajs <- trajectories(candidate.platelets)
matchTrajToParticles(candidate.platelets, trajs)

A sample `Frames` object

Description

The sample Frames object is constituted by a subset of a time-lapse intravital microscopy imaging dataset. Green channel marks leukocytes, red channel focuses on blood platelets. 20 frames are provided in this subset. Images are kindly provided by Sven Jaeckel ([email protected]).

Author(s)

Federico Marini, [email protected], 2014

Normalize the values of a `Frames` object

Description

Applies a transformation to the Frames object in a way that the intensities throughout the acquisition are normalized overall in term of pixel values sums. It can be used to compensate for example a global change in the illumination values, e.g. due to changed acquisition conditions in experiments that span long timescales.

Usage

normalizeFrames(frames, normFun = "median")
normalizeFrames(frames, normFun = "median")

Arguments

`frames`	A `Frames` object to normalize
`normFun`	The normalization function chosen. Can be one of `mean` or `median`

Value

A Frames object with normalized pixel values.

Author(s)

Federico Marini, [email protected], 2014

Examples

data(MesenteriumSubset)
normalizeFrames(MesenteriumSubset,normFun="median") 
data(MesenteriumSubset)
normalizeFrames(MesenteriumSubset,normFun="median")

Extracts particles from the images of a `Frames` object.

Description

Extracts particles from the images of a Frames object.

Usage

particles(
  raw.frames,
  binary.frames = NULL,
  channel = NULL,
  BPPARAM = bpparam()
)
particles(
  raw.frames,
  binary.frames = NULL,
  channel = NULL,
  BPPARAM = bpparam()
)

Arguments

`raw.frames`	A `Frames` object with the raw images (mandatory)
`binary.frames`	A `Frames` object with preprocessed images (optional, if not provided gets produced with standard default parameters)
`channel`	Character string. The channel to perform the operations on. Can be `red`, `green` or `blue`
`BPPARAM`	a `MulticoreParam` object, used to control the performances inside the `BiocParallel` call to process frames in parallel by taking advantage of the computing infrastructure available

Value

A ParticleSet object, containing all detected particles for each frame

Author(s)

Federico Marini, [email protected], 2015

Examples

data("MesenteriumSubset")

data("MesenteriumSubset")

ParticleSet class

Description

S4 class for storing information on particles detected in distinct frames.

Slots

.Data: A list storing the information for the particles
channel: A character vector, can be 'red','green', or 'blue'. It refers to which channel the particles were detected

Generate a penalty function

Description

A function to generate penalty functions to use while linking particles

Usage

penaltyFunctionGenerator(
  epsilon1 = 0.1,
  epsilon2 = 2,
  lambda1 = 1,
  lambda2 = 1
)
penaltyFunctionGenerator(
  epsilon1 = 0.1,
  epsilon2 = 2,
  lambda1 = 1,
  lambda2 = 1
)

Arguments

`epsilon1`	A numeric value, to be used in the formula. Jitter for allowing angular displacements
`epsilon2`	A numeric value, to be used in the formula. Jitter for allowing spatial displacements
`lambda1`	A numeric value. Multiplicative factor for the penalty function
`lambda2`	A numeric value. Multiplicative factor applied to the angular displacement

Value

A function object, to be used as penalty function

Author(s)

Federico Marini, [email protected], 2014

Examples

custom.function <- penaltyFunctionGenerator(epsilon1=0.1,epsilon2=6,lambda1=1.5,lambda2=0)

custom.function <- penaltyFunctionGenerator(epsilon1=0.1,epsilon2=6,lambda1=1.5,lambda2=0)

3D representation of a `TrajectorySet` object

Description

Provides a visual representation of a TrajectorySet object

Usage

## S3 method for class 'TrajectorySet'
plot(x, frames, verbose = FALSE, ...)
## S3 method for class 'TrajectorySet'
plot(x, frames, verbose = FALSE, ...)

Arguments

`x`	A `TrajectorySet` object
`frames`	A `Frames` object, used here to identify the limits of the region of interest
`verbose`	Logical, whether to provide additional output on the command line
`...`	Arguments to be passed to methods

Details

Based on the plotly library, the function extracts the region of interests from the dimensions of an image of the Frames object, and afterwards plots the x-y-time representation of the identified trajectories

Value

plot.TrajectorySet returns an invisible NULL.

Author(s)

Federico Marini, [email protected], 2014

Examples

data("MesenteriumSubset")
data("candidate.platelets")
platelets.trajectories <- trajectories(candidate.platelets)
## Not run: 
plot(platelets.trajectories,MesenteriumSubset)

## End(Not run)
data("MesenteriumSubset")
data("candidate.platelets")
platelets.trajectories <- trajectories(candidate.platelets)
## Not run: 
plot(platelets.trajectories,MesenteriumSubset)

## End(Not run)

2D projection of a `TrajectorySet` object

Description

Provides a bird's eye view of a TrajectorySet object on a bidimensional space

Usage

plot2D.TrajectorySet(
  trajectoryset,
  frames,
  trajIDs = NULL,
  addGrid = FALSE,
  verbose = FALSE,
  ...
)
plot2D.TrajectorySet(
  trajectoryset,
  frames,
  trajIDs = NULL,
  addGrid = FALSE,
  verbose = FALSE,
  ...
)

Arguments

`trajectoryset`	A `TrajectorySet` object
`frames`	A `Frames` object, used here to identify the limits of the region of interest
`trajIDs`	A vector containing the ids of the desired trajectories
`addGrid`	Logical, add an additional grid to the 2-dimensional plot (visual aid for backtracking trajectory point locations)
`verbose`	Logical, whether to provide additional output on the command line
`...`	Arguments to be passed to methods

Details

This function extracts the region of interests from the dimensions of an image of the Frames object, and afterwards plots the x-y-time representation of the identified trajectories on a 2d plane. It is possible to subset the TrajectorySet object with the IDs of the desired trajectories

Value

plot2D.TrajectorySet returns an invisible NULL.

Author(s)

Federico Marini, [email protected], 2014

Examples

data("MesenteriumSubset")
data("candidate.platelets")
platelets.trajectories <- trajectories(candidate.platelets)
plot2D.TrajectorySet(platelets.trajectories,MesenteriumSubset)

data("MesenteriumSubset")
data("candidate.platelets")
platelets.trajectories <- trajectories(candidate.platelets)
plot2D.TrajectorySet(platelets.trajectories,MesenteriumSubset)

Preprocessing function for `Frames` objects

Description

Frames objects are processed according to the chosen set of parameters. Many of them refer directly to existing EBImage functions, please see the corresponding help for additional information

Usage

preprocess.Frames(
  frames,
  brush.size = 3,
  brush.shape = "disc",
  at.offset = 0.15,
  at.wwidth = 10,
  at.wheight = 10,
  kern.size = 3,
  kern.shape = "disc",
  ws.tolerance = 1,
  ws.radius = 1,
  displayprocessing = FALSE,
  ...
)
preprocess.Frames(
  frames,
  brush.size = 3,
  brush.shape = "disc",
  at.offset = 0.15,
  at.wwidth = 10,
  at.wheight = 10,
  kern.size = 3,
  kern.shape = "disc",
  ws.tolerance = 1,
  ws.radius = 1,
  displayprocessing = FALSE,
  ...
)

Arguments

`frames`	A `Frames` object
`brush.size`	Size in pixels of the brush to be used for initial smoothing (low-pass filtering)
`brush.shape`	Shape of the brush to be used for initial smoothing (low-pass filtering)
`at.offset`	Offset to be used in the adaptive thresholding step - see also `thresh`. As an alternative thresholding method, see also `otsu` in the `EBImage` package.
`at.wwidth`	Width of the window for the adaptive thresholding step - see also `thresh`. As an alternative thresholding method, see also `otsu` in the `EBImage` package.
`at.wheight`	Height of the window for the adaptive thresholding step - see also `thresh`. As an alternative thresholding method, see also `otsu` in the `EBImage` package.
`kern.size`	Size in pixels of the kernel used for morphological operations - e.g., opening, which is an erosion followed by a dilation, and closing which is a dilation followed by an erosion - see also `opening`, `closing`
`kern.shape`	Shape of the kernel used for morphological operations
`ws.tolerance`	Tolerance allowed in performing the watershed-based segmentation (see also `watershed`)
`ws.radius`	Radius for the watershed-based segmentation (see also `watershed`)
`displayprocessing`	Logical, whether to display intermediate steps while performing preprocessing. Dismissed currently, it could increase runtime a lot
`...`	Arguments to be passed to methods

Value

A Frames object, whose frame images are the preprocessed versions of the input images

Author(s)

Federico Marini, [email protected], 2014

Examples

data("MesenteriumSubset")
preprocess.Frames(channel.Frames(MesenteriumSubset,"red"))

data("MesenteriumSubset")
preprocess.Frames(channel.Frames(MesenteriumSubset,"red"))

Constructor for a `Frames` object

Description

This function is used to create a Frames object from a vector of image files (or a folder specifying the directory containing them). The number of frames is also specified, as just a subset of the images can be used for this

Usage

read.Frames(image.files, nframes = NULL)
read.Frames(image.files, nframes = NULL)

Arguments

`image.files`	Vector of strings containing the locations where the (raw) images are to be found, or alternatively, the path to the folder
`nframes`	Number of frames that will constitute the `Frames` object

Value

An object of the Frames class, which holds the info on a list of frames, specifying for each the following elements:

`image`	The `Image` object containing the image itself
`location`	The complete path to the location of the original image

Author(s)

Federico Marini, [email protected], 2014

Examples

## see vignette
## Not run: fullData <- read.Frames(image.files = "/path/to/the/directory", nframes = 100)

## see vignette
## Not run: fullData <- read.Frames(image.files = "/path/to/the/directory", nframes = 100)

Constructor for a `ParticleSet` object

Description

This function is used to create a ParticleSet object from a vector/list of tab separated text files, each of one containing one line for each particle in the related frame, alongside with its coordinates and if available, the computed features The number of frames is also specified, as just a subset of the particle lists can be used for this

Usage

read.particles(particle.files, nframes = NULL)
read.particles(particle.files, nframes = NULL)

Arguments

`particle.files`	Vector of strings containing the locations where the particle coordinates are to be found, or alternatively, the path to the folder
`nframes`	Number of frames that will constitute the `ParticleSet` object

Value

An object of the ParticleSet class

Author(s)

Federico Marini, [email protected], 2014

Examples

## see vignette and export.particles

## see vignette and export.particles

Function equivalent for MATLAB's repmat - Replicate and tile arrays

Description

A more flexible and stylish alternative to replicate the behaviour of the repmat function of MATLAB

Usage

repmat(a, n, m)
repmat(a, n, m)

Arguments

`a`	The matrix to copy
`n`	The n value for the tiling
`m`	The m value for the tiling

Value

Creates a large matrix consisting of an m-by-n tiling of copies of a.

Author(s)

Robin Hankin, 2001

References

http://cran.r-project.org/doc/contrib/R-and-octave.txt

Rotates all images in a `Frames` object

Description

Rotation is performed exploiting the rotate function of the EBImage package. Could be automated if support for coordinate/pixel interaction is included

Usage

rotate.Frames(frames, angle, testing = FALSE)
rotate.Frames(frames, angle, testing = FALSE)

Arguments

`frames`	A `Frames` object
`angle`	The rotation angle (clockwise) specified in degrees
`testing`	Logical, whether to just test the rotation or to actually perform it. Default set to `FALSE`

Value

A Frames object containing the rotated frames

Author(s)

Federico Marini, [email protected], 2014

Examples

data("MesenteriumSubset")
rotate.Frames(MesenteriumSubset,angle = 40)

data("MesenteriumSubset")
rotate.Frames(MesenteriumSubset,angle = 40)

Extracts subsets of frames from a `Frames` object

Description

An input Frames object is subject to subsetting. This function is useful e.g. when the trajectory of interest is presenting gaps (i.e. does not actually include a frame)

Usage

select.Frames(frames, framesToKeep = 1, ...)
select.Frames(frames, framesToKeep = 1, ...)

Arguments

`frames`	A `Frames` object
`framesToKeep`	A vector containing the indexes of the frames to keep in the selection
`...`	Arguments to be passed to methods

Value

A Frames object, composed by the subset of frames of the input Frames

Author(s)

Federico Marini, [email protected], 2014

Examples

data("MesenteriumSubset")
select.Frames(MesenteriumSubset, framesToKeep = c(1:10, 14:20))

data("MesenteriumSubset")
select.Frames(MesenteriumSubset, framesToKeep = c(1:10, 14:20))

Performs filtering on a `ParticleSet` object

Description

According to parameters of interests, such as size, eccentricity/shape, filters out the particles that do not satisfy the indicated requirements

Usage

select.particles(particleset, min.area = 1, max.area = 1000)
select.particles(particleset, min.area = 1, max.area = 1000)

Arguments

`particleset`	A `ParticleSet` object. A `LinkedParticleSet` object can also be provided as input, yet the returned object will be a `ParticleSet` object that needs to be linked again
`min.area`	Size in pixels of the minimum area needed to detect the object as a potential particle of interest
`max.area`	Size in pixels of the maximum area allowed to detect the object as a potential particle of interest

Value

A ParticleSet object

Author(s)

Federico Marini, [email protected], 2014

Examples

data("candidate.platelets")
selected.platelets <- select.particles(candidate.platelets, min.area = 5)
selected.platelets

data("candidate.platelets")
selected.platelets <- select.particles(candidate.platelets, min.area = 5)
selected.platelets

Shiny application for exploring the features and parameters provided by `flowcatchR`

Description

Launches a Shiny Web Application for interactive data exploration. Default data loaded are the frames from the MesenteriumSubset object, custom values can be inserted by typing the location of the data stored in a local folder. The Application is structured in a variety of tabs that mirror the steps in the usual workflow in time-lapse microscopy images. These can allow the user to interactively explore the parameters and their effect in the reactive framework provided by Shiny.

Usage

shinyFlow()
shinyFlow()

Value

The Shiny Application is launched in the web browser

Author(s)

Federico Marini, [email protected], 2015

Examples

## Not run: shinyFlow()
## Not run: shinyFlow()

Display conveniently a `Frames` object

Description

Display conveniently a Frames object

Usage

## S4 method for signature 'Frames'
show(object)
## S4 method for signature 'Frames'
show(object)

Arguments

object

A Frames object

Value

This returns an invisible NULL.

Author(s)

Federico Marini, [email protected], 2014

Examples

data("MesenteriumSubset")
print(MesenteriumSubset)
data("MesenteriumSubset")
print(MesenteriumSubset)

Displaying conveniently a `KinematicsFeatures` object

Description

Displaying conveniently a KinematicsFeatures object

Usage

## S4 method for signature 'KinematicsFeatures'
show(object)
## S4 method for signature 'KinematicsFeatures'
show(object)

Arguments

object

A KinematicsFeatures object

Value

This returns an invisible NULL.

Author(s)

Federico Marini, [email protected], 2014

Examples

data("candidate.platelets")
platelets.trajectories <- trajectories(candidate.platelets)
traj11features <- kinematics(platelets.trajectories,trajectoryIDs = 11)
print(traj11features)

data("candidate.platelets")
platelets.trajectories <- trajectories(candidate.platelets)
traj11features <- kinematics(platelets.trajectories,trajectoryIDs = 11)
print(traj11features)

Display conveniently a `KinematicsFeatureSet` object

Description

Display conveniently a KinematicsFeatureSet object

Usage

## S4 method for signature 'KinematicsFeaturesSet'
show(object)
## S4 method for signature 'KinematicsFeaturesSet'
show(object)

Arguments

object

A KinematicsFeatureSet object

Value

This returns an invisible NULL.

Author(s)

Federico Marini, [email protected], 2014

Examples

data("candidate.platelets")
platelets.trajectories <- trajectories(candidate.platelets)
alltrajs.features <- kinematics(platelets.trajectories)
print(alltrajs.features)

data("candidate.platelets")
platelets.trajectories <- trajectories(candidate.platelets)
alltrajs.features <- kinematics(platelets.trajectories)
print(alltrajs.features)

Display conveniently a `LinkedParticleSet` object

Description

Display conveniently a LinkedParticleSet object

Usage

## S4 method for signature 'LinkedParticleSet'
show(object)
## S4 method for signature 'LinkedParticleSet'
show(object)

Arguments

object

A LinkedParticleSet object

Value

This returns an invisible NULL.

Author(s)

Federico Marini, [email protected], 2014

Examples

data("candidate.platelets")
linked.platelets <- link.particles(candidate.platelets,L=26,R=3,epsilon1=0,
epsilon2=0,lambda1=1,lambda2=0,penaltyFunction=penaltyFunctionGenerator(),
include.area=FALSE)
print(linked.platelets)

data("candidate.platelets")
linked.platelets <- link.particles(candidate.platelets,L=26,R=3,epsilon1=0,
epsilon2=0,lambda1=1,lambda2=0,penaltyFunction=penaltyFunctionGenerator(),
include.area=FALSE)
print(linked.platelets)

Display conveniently a `ParticleSet` object

Description

Display conveniently a ParticleSet object

Usage

## S4 method for signature 'ParticleSet'
show(object)
## S4 method for signature 'ParticleSet'
show(object)

Arguments

object

A ParticleSet object

Value

This returns an invisible NULL.

Author(s)

Federico Marini, [email protected], 2014

Examples

data("candidate.platelets")
print(candidate.platelets)

data("candidate.platelets")
print(candidate.platelets)

Display conveniently a `TrajectorySet` object

Description

Display conveniently a TrajectorySet object

Usage

## S4 method for signature 'TrajectorySet'
show(object)
## S4 method for signature 'TrajectorySet'
show(object)

Arguments

object

A TrajectorySet object

Value

This returns an invisible NULL.

Author(s)

Federico Marini, [email protected], 2014

Examples

data("candidate.platelets")
platelets.trajectories <- trajectories(candidate.platelets)
print(platelets.trajectories)

data("candidate.platelets")
platelets.trajectories <- trajectories(candidate.platelets)
print(platelets.trajectories)

Snap the features of the closest particle identified

Description

This function combines all classes related to a single experiment in order to deliver a clickable feedback on one of the frames.

Usage

snap(
  raw.frames,
  binary.frames,
  particleset,
  trajectoryset,
  frameID = 1,
  infocol = "yellow",
  infocex = 1,
  showVelocity = FALSE
)
snap(
  raw.frames,
  binary.frames,
  particleset,
  trajectoryset,
  frameID = 1,
  infocol = "yellow",
  infocex = 1,
  showVelocity = FALSE
)

Arguments

`raw.frames`	A `Frames` object with the raw frames data
`binary.frames`	A `Frames` object with the preprocessed frames data
`particleset`	A `ParticleSet` object with the particles data
`trajectoryset`	A `TrajectorySet` object with the trajectories data
`frameID`	The ID of the frame to inspect
`infocol`	The color to use for plotting the contours and the information on the clicked particle
`infocex`	The numeric character expansion value as in `cex` to be used for printing the text on the image
`showVelocity`	Logical, whether to display additional information on the instantaneous velocity of the particle

Value

An image of the selected frame, rendered in R native graphics, and additionally a list with the coordinates as well as the trajectory ID of the particle closest to the clicked location

Author(s)

Federico Marini, [email protected], 2015

Examples

## Not run: data(MesenteriumSubset)
binary.frames <- preprocess.Frames(channel.Frames(MesenteriumSubset,"red"))
particleset <- particles(MesenteriumSubset,binary.frames,"red")
trajectoryset <- trajectories(particleset)
snap(MesenteriumSubset,binary.frames,particleset,trajectoryset,frameID=1)

## End(Not run)
## Not run: data(MesenteriumSubset)
binary.frames <- preprocess.Frames(channel.Frames(MesenteriumSubset,"red"))
particleset <- particles(MesenteriumSubset,binary.frames,"red")
trajectoryset <- trajectories(particleset)
snap(MesenteriumSubset,binary.frames,particleset,trajectoryset,frameID=1)

## End(Not run)

Converts polar coordinates to cartesian coordinates

Description

Conversion from (radius,theta) to (x,y)

Usage

toCartesianCoords(Theta, Radius)
toCartesianCoords(Theta, Radius)

Arguments

`Theta`	The Theta angle
`Radius`	The radius value in polar coordinates

Value

A list containing Theta and Radius, as in polar coordinates

Author(s)

Federico Marini, [email protected], 2014

Converts cartesian coordinates to polar coordinates

Description

Conversion from (x,y) to (radius,theta)

Usage

toPolarCoords(x, y)
toPolarCoords(x, y)

Arguments

`x`	x coordinate
`y`	y coordinate

Value

A list containing Theta and Radius, as in polar coordinates

Author(s)

Federico Marini, [email protected], 2014

Generate trajectories

Description

Generates a TrajectorySet object from a (Linked)ParticleSet

Usage

trajectories(particleset, verbose = FALSE, ...)
trajectories(particleset, verbose = FALSE, ...)

Arguments

`particleset`	A (`Linked`)`ParticleSet` object
`verbose`	Logical, currently not used - could be introduced for providing additional info on the trajectories
`...`	Arguments to be passed to methods

Value

A TrajectorySet object

Author(s)

Federico Marini, [email protected], 2014

Examples

data("candidate.platelets")
platelets.trajectories <- trajectories(candidate.platelets)

data("candidate.platelets")
platelets.trajectories <- trajectories(candidate.platelets)

TrajectorySet class

Description

S4 class for storing information on the trajectories identified, including whether there were gaps, the number of points, and more

Slots

.Data: A list storing the information for the particles
channel: A character vector, can be 'red','green', or 'blue'. It refers to which channel the particles were detected

Package 'flowcatchR'

Help Index

Add object contours to a Frames object Creates a Frames object containing raw information, combined with the segmented images and the relative trajectory under analysis

Description

Usage

Arguments

Value

Author(s)

Examples

Combines the information from a raw Frames object and the corresponding preprocessed one

Description

Usage

Arguments

Value

Author(s)

Info on the dimensions of the FOV

Description

Usage

Arguments

Value

Author(s)

A sample ParticleSet object

Description

Author(s)

Channel extraction for objects

Description

Usage

Arguments

Value

Examples

Calculates the Mean Squared Displacement for a trajectory

Description

Usage

Arguments

Value

Author(s)

Cut borders of a Frames object

Description

Usage

Arguments

Details

Value

Author(s)

Examples

Exports a Frames object

Description

Usage

Arguments

Value

Author(s)

Examples

Exports a ParticleSet object

Description

Usage

Arguments

Value

Author(s)

Examples

Calculate a set of kinematics parameters from a single trajectory

Description

Usage

Arguments

Value

Author(s)

flowcatchR: analyzing time-lapse microscopy imaging, from detection to tracking

Description

Details

Author(s)

Constructor for a Frames object

Description

Usage

Arguments

Value

Author(s)

Examples

Frames class

Description

Slots

Initialize a ParticleSet object for subsequent linking/tracking

Description

Add object contours to a `Frames` object Creates a `Frames` object containing raw information, combined with the segmented images and the relative trajectory under analysis

Combines the information from a raw `Frames` object and the corresponding preprocessed one

A sample `ParticleSet` object

Channel extraction for `objects`

Cut borders of a `Frames` object

Exports a `Frames` object

Exports a `ParticleSet` object

Constructor for a `Frames` object

Initialize a `ParticleSet` object for subsequent linking/tracking

Explore the frames of a `Frames`

Calculate a set of kinematics parameter from a `TrajectorySet` object, or a single parameter, or from a single trajectory (all possible combinations)

Compute the length of render frames in a `Frames` object

Links a `ParticleSet` object

A sample `Frames` object

Normalize the values of a `Frames` object

Extracts particles from the images of a `Frames` object.