## ----style-knitr, eval=TRUE, echo=FALSE, results="asis"------------------
BiocStyle::latex()
## ----setup, include=FALSE, cache=FALSE, eval=TRUE, echo=FALSE------------
library(knitr)
opts_chunk$set(fig.path='./figures/flowcatchR-',
fig.align='center', fig.show='asis', #fig.show='hold',dev="png",
eval=TRUE,
fig.width=4.5,
fig.height=4.5,
message=FALSE,
size='small',
comment='##',
prompt=FALSE,
echo=TRUE, # set to true for the vignette!
results='hold',
tidy=FALSE)
options(replace.assign=TRUE,width=80,'reindent.spaces'=2) # for tidying up the code
# options(rgl.useNULL=TRUE)
# knit_hooks$set(rgl=hook_rgl)
## ----install,eval=FALSE--------------------------------------------------
## source("http://bioconductor.org/biocLite.R")
## biocLite("flowcatchR")
## ----install-devel,eval=FALSE--------------------------------------------
## install.packages("devtools") # if needed
## devtools::install_github("federicomarini/flowcatchR")
## ----helpmaintainer------------------------------------------------------
maintainer("flowcatchR")
## ----citationPkg---------------------------------------------------------
citation("flowcatchR")
## ----loadData,results='hide',message=TRUE--------------------------------
library("flowcatchR")
data("MesenteriumSubset")
## ----meseLoaded----------------------------------------------------------
# printing summary information for the MesenteriumSubset object
MesenteriumSubset
## ----workflowCompact,eval=FALSE,results='hide'---------------------------
## # one command to seize them all :)
## fullResults <- kinematics(trajectories(particles(channel.Frames(MesenteriumSubset,"red"))))
## ----newFrames,eval=FALSE------------------------------------------------
## # initialization
## fullData <- read.Frames(image.files="/path/to/folder/containing/images/", nframes=100)
## # printing summary information for the Frames object
## fullData
## ----inspectRaw,fig.height=4,fig.width=7.5,fig.cap="The first 9 frames of the MesenteriumSubset dataset. The red channel stores information about platelets, while the green channel is dedicated to leukocytes"----
inspect.Frames(MesenteriumSubset, nframes=9, display.method="raster")
## ----selectRed-----------------------------------------------------------
plateletsMesenterium <- channel.Frames(MesenteriumSubset, mode="red")
plateletsMesenterium
## ----inspectPlatelets,fig.height=4,fig.width=7.5,fig.cap="The first 9 frames of the MesenteriumSubset dataset, just displaying the GrayScale signal for the red channel stored in plateletsMesenterium (for the thrombocytes)"----
inspect.Frames(plateletsMesenterium, nframes=9, display.method="raster")
## ----segmentPreprocess---------------------------------------------------
preprocessedPlatelets <- preprocess.Frames(plateletsMesenterium,
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)
preprocessedPlatelets
## ----inspectSegm,fig.height=4,fig.width=7.5,fig.cap="The first 9 frames after preprocessing of the MesenteriumSubset dataset. The binarized image shows the detected objects after thresholding."----
inspect.Frames(preprocessedPlatelets, nframes=9, display.method="raster")
## ----cropFrames----------------------------------------------------------
croppedFrames <- crop.Frames(plateletsMesenterium,
cutLeft=6, cutRight=6,
cutUp=3, cutDown=3,
testing=FALSE)
croppedFrames
## ----rotateFrames--------------------------------------------------------
rotatedFrames <- rotate.Frames(plateletsMesenterium, angle=30)
rotatedFrames
## ----selectFrames--------------------------------------------------------
subsetFrames <- select.Frames(plateletsMesenterium,
framesToKeep=c(1:10,14:20))
subsetFrames
## ----normalizeFrames-----------------------------------------------------
normFrames <- normalizeFrames(plateletsMesenterium,normFun = "median")
## ----particleSet---------------------------------------------------------
platelets <- particles(plateletsMesenterium, preprocessedPlatelets)
platelets
## ----selectParticles-----------------------------------------------------
selectedPlatelets <- select.particles(platelets, min.area=3)
selectedPlatelets
## ----checkSelection,fig.height=4,fig.width=7.5,fig.cap="Particles detected in the first 9 frames are shown in yellow, with their contours defined by the segmentation procedure."----
paintedPlatelets <- add.contours(raw.frames=MesenteriumSubset,
binary.frames=preprocessedPlatelets,
mode="particles")
inspect.Frames(paintedPlatelets, nframes=9, display.method="raster")
## ----penFunc-------------------------------------------------------------
defaultPenalty <- penaltyFunctionGenerator()
print(defaultPenalty)
## ----linkParticles-------------------------------------------------------
linkedPlatelets <- link.particles(platelets,
L=26, R=3,
epsilon1=0, epsilon2=0,
lambda1=1, lambda2=0,
penaltyFunction=penaltyFunctionGenerator(),
include.area=FALSE)
linkedPlatelets
## ----expo-impo,eval=FALSE------------------------------------------------
## # export to csv format
## export.particles(platelets, dir="/path/to/export/folder/exportParticleSet/")
## # re-import the previously exported, in this case
## importedPlatelets <- read.particles(particle.files="/path/to/export/folder/exportParticleSet/")
##
## ----generateTrajs-------------------------------------------------------
trajPlatelets <- trajectories(linkedPlatelets)
trajPlatelets
## ----cubeTrajs,fig.cap="A 2D+time representation of the trajectories, produced by plotting a TrajectoryList object",eval=FALSE----
## plot(trajPlatelets, MesenteriumSubset)
## ----overviewTrajs,fig.height=4,fig.width=7.5,fig.cap='A 2D "flat" representation of the trajectories, more suitable to give an indication of the global movement'----
plot2D.TrajectorySet(trajPlatelets, MesenteriumSubset)
## ----contourTrajs--------------------------------------------------------
paintedTrajectories <- add.contours(raw.frames=MesenteriumSubset,
binary.frames=preprocessedPlatelets,
trajectoryset=trajPlatelets,
mode="trajectories")
paintedTrajectories
## ----inspectTrajs,fig.height=4,fig.width=7.5,fig.cap="Particles detected in the first 9 frames are shown this time in colours corresponding to the identified trajectories, again with their contours defined by the segmentation procedure."----
inspect.Frames(paintedTrajectories,nframes=9,display.method="raster")
## ----traj11,fig.height=4,fig.width=7.5,fig.cap="First 9 frames for trajectory with ID 11, as supplied to the trajIds argument of add.contours"----
traj11 <- add.contours(raw.frames=MesenteriumSubset,
binary.frames=preprocessedPlatelets,
trajectoryset=trajPlatelets,
mode="trajectories",
trajIDs=11)
traj11
inspect.Frames(traj11, nframes=9, display.method="raster")
## ----viewTraj11----------------------------------------------------------
trajPlatelets[[11]]
## ----exportTraj11,eval=FALSE---------------------------------------------
## export.Frames(traj11, dir=tempdir(), nameStub="vignetteTest_traj11",
## createGif=TRUE, removeAfterCreatingGif=FALSE)
## ----loopExport, cache=TRUE,eval=FALSE-----------------------------------
## evaluatedTrajectories <- trajPlatelets
##
## for(i in 1:length(trajPlatelets))
## {
## paintedTraj <- add.contours(raw.frames=MesenteriumSubset,
## binary.frames=preprocessedPlatelets,
## trajectoryset=trajPlatelets,
## mode="trajectories",
## col="yellow",
## trajIDs=i)
## export.Frames(paintedTraj,
## nameStub=paste0("vignetteTest_evaluation_traj_oneByOne_",i),
## createGif=TRUE, removeAfterCreatingGif=TRUE)
## ### uncomment the code below to perform the interactive evaluation of the single trajectories
##
## # cat("Should I keep this trajectory? --- 0: NO, 1:YES --- no other values allowed")
## # userInput <- readLines(n=1L)
## # ## if neither 0 nor 1, do not update
## # ## otherwise, this becomes the value for the field keep in the new TrajectoryList
## # evaluatedTrajectories@.Data[[i]]$keep <- as.logical(as.numeric(userInput))
## }
## ----kinemFeats----------------------------------------------------------
allKinematicFeats.allPlatelets <- kinematics(trajPlatelets,
trajectoryIDs=NULL, # will select all trajectory IDs
acquisitionFrequency=30, # value in milliseconds
scala=50, # 1 pixel is equivalent to ... micrometer
feature=NULL) # all kinematic features available
## ----kinemInspect--------------------------------------------------------
allKinematicFeats.allPlatelets
## ----kinemFeatsAvailable-------------------------------------------------
allKinematicFeats.allPlatelets <- kinematics(trajPlatelets, feature="?")
## ----allVelos,fig.cap="Histogram of the curvilinear velocities for all trajectories identified in the MesenteriumSubset dataset",warning=FALSE----
allVelocities <- kinematics(trajPlatelets, feature="curvilinearVelocity")
hist(allVelocities, breaks=10, probability=TRUE, col="cadetblue",
xlab="Curvilinear Velocities Distribution",
main="Trajectory Analysis: Curvilinear Velocities")
lines(density(allVelocities, na.rm=TRUE), col="steelblue", lwd=2)
## ----snapFrames,eval=FALSE-----------------------------------------------
## snap(MesenteriumSubset,preprocessedPlatelets,
## platelets,trajPlatelets,
## frameID = 1,showVelocity = T)
## ----snapExample,echo=FALSE,fig.width=7,fig.cap="Output generated by the snap function, where the user wanted to identify the particle and additionally display the trajectory information (ID, instantaneous velocity) on it."----
display(readImage(system.file("extdata/snapExp.jpg",package="flowcatchR")),
method = "raster")
## ----launchShiny,eval=FALSE----------------------------------------------
## shinyFlow()
## ----notebooksLocation---------------------------------------------------
list.files(system.file("extdata",package = "flowcatchR"),pattern = "*.ipynb")
## ----ipynb,eval=FALSE----------------------------------------------------
## $ ipython notebook
## ----sessioininfo,results='asis'-----------------------------------------
toLatex(sessionInfo())