Package 'CytoPipelineGUI' reference manual

Title:	GUI's for visualization of flow cytometry data analysis pipelines
Description:	This package is the companion of the `CytoPipeline` package. It provides GUI's (shiny apps) for the visualization of flow cytometry data analysis pipelines that are run with `CytoPipeline`. Two shiny applications are provided, i.e. an interactive flow frame assessment and comparison tool and an interactive scale transformations visualization and adjustment tool.
Authors:	Philippe Hauchamps [aut, cre] , Laurent Gatto [aut] , Dan Lin [ctb]
Maintainer:	Philippe Hauchamps <[email protected]>
License:	GPL-3
Version:	1.5.0
Built:	2024-11-18 03:26:12 UTC
Source:	https://github.com/bioc/CytoPipelineGUI

interactive visualization of flow cytometry data analysis pipeline objects stored in cache

Description

interactive visualization of flow cytometry data analysis pipeline objects stored in cache

Usage

CytoPipelineCheckApp(dir = ".", debug = FALSE)
CytoPipelineCheckApp(dir = ".", debug = FALSE)

Arguments

`dir`	the root directory into which the engine will look for existing CytoPipeline experiments
`debug`	if TRUE, will output messages on the console tracking the shiny events, for debugging purposes

Value

no return value

Examples


# run CytoPipeline object first

outputDir <- base::tempdir()


rawDataDir <-
    system.file("extdata", package = "CytoPipeline")
experimentName <- "OMIP021_PeacoQC"
sampleFiles <- 
    file.path(
        rawDataDir, 
        list.files(
            rawDataDir, 
            pattern = "Donor"))
jsonDir <- system.file("extdata", package = "CytoPipeline")
jsonPath <- file.path(jsonDir, "pipelineParams.json")

pipL2 <- CytoPipeline(
    jsonPath,
    experimentName = experimentName,
    sampleFiles = sampleFiles)

suppressWarnings(execute(
    pipL2,
    rmCache = TRUE,
    path = outputDir))

# run shiny app

if (interactive())
    CytoPipelineCheckApp(dir = outputDir)                    

# run CytoPipeline object first

outputDir <- base::tempdir()


rawDataDir <-
    system.file("extdata", package = "CytoPipeline")
experimentName <- "OMIP021_PeacoQC"
sampleFiles <- 
    file.path(
        rawDataDir, 
        list.files(
            rawDataDir, 
            pattern = "Donor"))
jsonDir <- system.file("extdata", package = "CytoPipeline")
jsonPath <- file.path(jsonDir, "pipelineParams.json")

pipL2 <- CytoPipeline(
    jsonPath,
    experimentName = experimentName,
    sampleFiles = sampleFiles)

suppressWarnings(execute(
    pipL2,
    rmCache = TRUE,
    path = outputDir))

# run shiny app

if (interactive())
    CytoPipelineCheckApp(dir = outputDir)

Plot the difference plot between two flow frames from a CytoPipeline run

Description

Based on an experiment name, this function will gather the required flowFrames from the CytoPipeline disk cache and display a difference plot using the user chosen 1D or 2D view.

Usage

plotDiffFlowFrame(
  experimentNameFrom,
  experimentNameTo,
  whichQueueFrom,
  whichQueueTo,
  sampleFileFrom,
  sampleFileTo,
  path,
  flowFrameNameFrom,
  flowFrameNameTo,
  xChannelLabelFrom,
  xChannelLabelTo,
  yChannelLabelFrom,
  yChannelLabelTo,
  interactive = FALSE,
  useAllCells,
  nDisplayCells,
  useFixedLinearRange,
  linearRange,
  transfoListName = " "
)
plotDiffFlowFrame(
  experimentNameFrom,
  experimentNameTo,
  whichQueueFrom,
  whichQueueTo,
  sampleFileFrom,
  sampleFileTo,
  path,
  flowFrameNameFrom,
  flowFrameNameTo,
  xChannelLabelFrom,
  xChannelLabelTo,
  yChannelLabelFrom,
  yChannelLabelTo,
  interactive = FALSE,
  useAllCells,
  nDisplayCells,
  useFixedLinearRange,
  linearRange,
  transfoListName = " "
)

Arguments

`experimentNameFrom`	the experiment name (representing a pipeline run) from which to extract the flow frame ('from' situation)
`experimentNameTo`	the experiment name (representing a pipeline run) from which to extract the flow frame ('to' situation)
`whichQueueFrom`	"pre-processing" or "scale transform" ('from' situation)
`whichQueueTo`	"pre-processing" or "scale transform" ('to' situation)
`sampleFileFrom`	in case 'whichQueueFrom' is set to 'pre-processing, which sample file to look at for the 'from' situation. This can be a number or a character. if whichQueueFrom == "scale transform", the sampleFileFrom is ignored if NULL and whihQueueFrom == "pre-processing", the sampleFileFrom is defaulted to the first one belonging to the experiment
`sampleFileTo`	same as sampleFileFrom, but for the 'to' situation
`path`	the root path to look for the CytoPipeline experiment cache
`flowFrameNameFrom`	for the 'from' situation, the name of the object to fetch (as referenced in the pipeline workflow)
`flowFrameNameTo`	for the 'to' situation, the name of the object to fetch (as referenced in the pipeline workflow)
`xChannelLabelFrom`	the label of the channel to be displayed on the x axis: the conventional syntax is : `channelName` + " - " + `channelMarker`
`xChannelLabelTo`	should be equal to xChannelLabelFrom (otherwise no plot is returned but NULL)
`yChannelLabelFrom`	the label of the channel to be displayed on the y axis: the conventional syntax is : `channelName` + " - " + `channelMarker`
`yChannelLabelTo`	should be equal to yChannelLabelFrom (otherwise no plot is returned but NULL)
`interactive`	if TRUE, uses ggplot_shiny
`useAllCells`	if TRUE, no subsampling will be done
`nDisplayCells`	if useAllCells == FALSE, the number of subsampled cells
`useFixedLinearRange`	if TRUE, all channels using a linear scale will use a fixed range set by linearRange
`linearRange`	set for all channels using a linear scale, if useFixedLinearRange == TRUE
`transfoListName`	if not set to " ", the transformation list (as an object name ending with "_obj", as referenced in the pipeline workflow) to be used for for display.

Value

a ggplot (or plotly if interactive = TRUE) object

Examples


# run CytoPipeline object first

outputDir <- base::tempdir()


rawDataDir <-
    system.file("extdata", package = "CytoPipeline")
experimentName <- "OMIP021_PeacoQC"
sampleFiles <- 
    file.path(
        rawDataDir, 
        list.files(rawDataDir, pattern = "Donor"))
jsonDir <- system.file("extdata", package = "CytoPipeline")
jsonPath <- file.path(jsonDir, "pipelineParams.json")

pipL2 <- CytoPipeline(
    jsonPath,
    experimentName = experimentName,
    sampleFiles = sampleFiles)

suppressWarnings(execute(
    pipL2,
    rmCache = TRUE,
    path = outputDir))


plotDiffFlowFrame(
    experimentNameFrom = experimentName,
    whichQueueFrom = "pre-processing",
    sampleFileFrom = 1,
    flowFrameNameFrom = "remove_doublets_obj",
    xChannelLabelFrom = "FSC-A : NA",
    yChannelLabelFrom = "SSC-A : NA",
    path = outputDir,
    experimentNameTo = experimentName,
    whichQueueTo = "pre-processing",
    sampleFileTo = 1,
    flowFrameNameTo = "remove_debris_obj",
    xChannelLabelTo = "FSC-A : NA",
    yChannelLabelTo = "SSC-A : NA",
    useAllCells = TRUE,
    nDisplayCells = 0,
    useFixedLinearRange = TRUE,
    linearRange = c(-100, 262144))

plotDiffFlowFrame(
    experimentNameFrom = experimentName,
    whichQueueFrom = "pre-processing",
    sampleFileFrom = 1,
    flowFrameNameFrom = "remove_doublets_obj",
    xChannelLabelFrom = "FSC-A : NA",
    yChannelLabelFrom = "SSC-A : NA",
    path = outputDir,
    experimentNameTo = experimentName,
    whichQueueTo = "pre-processing",
    sampleFileTo = 1,
    flowFrameNameTo = "remove_debris_obj",
    xChannelLabelTo = "FSC-A : NA",
    yChannelLabelTo = "SSC-A : NA",
    useAllCells = FALSE,
    nDisplayCells = 100,
    useFixedLinearRange = FALSE,
    linearRange = NULL)

plotDiffFlowFrame(
    experimentNameFrom = experimentName,
    whichQueueFrom = "pre-processing",
    sampleFileFrom = 1,
    flowFrameNameFrom = "remove_debris_obj",
    xChannelLabelFrom = "FSC-A : NA",
    yChannelLabelFrom = "Comp-525/50Violet-A : L/D Aqua - Viability",
    path = outputDir,
    experimentNameTo = experimentName,
    whichQueueTo = "pre-processing",
    sampleFileTo = 1,
    flowFrameNameTo = "remove_dead_cells_obj",
    xChannelLabelTo = "FSC-A : NA",
    yChannelLabelTo = "Comp-525/50Violet-A : L/D Aqua - Viability",
    useAllCells = TRUE,
    nDisplayCells = 0,
    useFixedLinearRange = FALSE,
    linearRange = NULL,
    transfoListName = "scale_transform_estimate_obj")   

# run CytoPipeline object first

outputDir <- base::tempdir()


rawDataDir <-
    system.file("extdata", package = "CytoPipeline")
experimentName <- "OMIP021_PeacoQC"
sampleFiles <- 
    file.path(
        rawDataDir, 
        list.files(rawDataDir, pattern = "Donor"))
jsonDir <- system.file("extdata", package = "CytoPipeline")
jsonPath <- file.path(jsonDir, "pipelineParams.json")

pipL2 <- CytoPipeline(
    jsonPath,
    experimentName = experimentName,
    sampleFiles = sampleFiles)

suppressWarnings(execute(
    pipL2,
    rmCache = TRUE,
    path = outputDir))


plotDiffFlowFrame(
    experimentNameFrom = experimentName,
    whichQueueFrom = "pre-processing",
    sampleFileFrom = 1,
    flowFrameNameFrom = "remove_doublets_obj",
    xChannelLabelFrom = "FSC-A : NA",
    yChannelLabelFrom = "SSC-A : NA",
    path = outputDir,
    experimentNameTo = experimentName,
    whichQueueTo = "pre-processing",
    sampleFileTo = 1,
    flowFrameNameTo = "remove_debris_obj",
    xChannelLabelTo = "FSC-A : NA",
    yChannelLabelTo = "SSC-A : NA",
    useAllCells = TRUE,
    nDisplayCells = 0,
    useFixedLinearRange = TRUE,
    linearRange = c(-100, 262144))

plotDiffFlowFrame(
    experimentNameFrom = experimentName,
    whichQueueFrom = "pre-processing",
    sampleFileFrom = 1,
    flowFrameNameFrom = "remove_doublets_obj",
    xChannelLabelFrom = "FSC-A : NA",
    yChannelLabelFrom = "SSC-A : NA",
    path = outputDir,
    experimentNameTo = experimentName,
    whichQueueTo = "pre-processing",
    sampleFileTo = 1,
    flowFrameNameTo = "remove_debris_obj",
    xChannelLabelTo = "FSC-A : NA",
    yChannelLabelTo = "SSC-A : NA",
    useAllCells = FALSE,
    nDisplayCells = 100,
    useFixedLinearRange = FALSE,
    linearRange = NULL)

plotDiffFlowFrame(
    experimentNameFrom = experimentName,
    whichQueueFrom = "pre-processing",
    sampleFileFrom = 1,
    flowFrameNameFrom = "remove_debris_obj",
    xChannelLabelFrom = "FSC-A : NA",
    yChannelLabelFrom = "Comp-525/50Violet-A : L/D Aqua - Viability",
    path = outputDir,
    experimentNameTo = experimentName,
    whichQueueTo = "pre-processing",
    sampleFileTo = 1,
    flowFrameNameTo = "remove_dead_cells_obj",
    xChannelLabelTo = "FSC-A : NA",
    yChannelLabelTo = "Comp-525/50Violet-A : L/D Aqua - Viability",
    useAllCells = TRUE,
    nDisplayCells = 0,
    useFixedLinearRange = FALSE,
    linearRange = NULL,
    transfoListName = "scale_transform_estimate_obj")

Plot a flow frame in 1D with explicit user given scale transform

Description

This function plots a 1D view, i.e. the marginal distribution for one specified channel, of the given flow frame, using the specific user-provided scale transformation parameters.

Usage

plotScaleTransformedChannel(
  ff,
  channel,
  applyTransform = c("axis scale only", "data"),
  transfoType = c("linear", "logicle"),
  linA,
  linB,
  negDecades,
  width,
  posDecades
)
plotScaleTransformedChannel(
  ff,
  channel,
  applyTransform = c("axis scale only", "data"),
  transfoType = c("linear", "logicle"),
  linA,
  linB,
  negDecades,
  width,
  posDecades
)

Arguments

`ff`	the `flowFrame` to be plotted
`channel`	the name of the channel of which to display the marginal distribution (i.e. the channel name used as column in the ff expression matrix).
`applyTransform`	if "data", data are explicitly transformed using the user provided sclae transformation parameters, before display if "axis scale only" (default), the data are not transformed, i.e. only the x axis scale is defined according to the scale transformation parameters.
`transfoType`	the transformation type, currently only `linear` and `logicle`(bi-exponential) are supported.
`linA`	the intercept parameter of the linear transformation.
`linB`	the slope parameter of the linear transformation.
`negDecades`	the number of additional decades on the negative side for the logicle transformation.
`width`	the width parameter of the logicle transformation.
`posDecades`	the number of positive decades of the logicle tranformation.

Value

a ggplot object

Examples

# run CytoPipeline object first

outputDir <- base::tempdir()


rawDataDir <-
    system.file("extdata", package = "CytoPipeline")
experimentName <- "OMIP021_PeacoQC"
sampleFiles <- 
    file.path(
        rawDataDir, 
        list.files(rawDataDir, pattern = "Donor"))
jsonDir <- system.file("extdata", package = "CytoPipeline")
jsonPath <- file.path(jsonDir, "pipelineParams.json")

pipL2 <- CytoPipeline(
    jsonPath,
    experimentName = experimentName,
    sampleFiles = sampleFiles)

suppressWarnings(execute(
    pipL2,
    rmCache = TRUE,
    path = outputDir))

ff <- CytoPipeline::getCytoPipelineFlowFrame(
pipL2,
path = outputDir,
whichQueue = "scale transform",
objectName = "flowframe_aggregate_obj"
)

plotScaleTransformedChannel(
    ff,
    channel = "FSC-A",
    transfoType = "linear",
    linA = 0.0002,
    linB = -0.5)

plotScaleTransformedChannel(
    ff,
    channel = "Comp-670/30Violet-A",
    transfoType = "logicle",
    negDecades = 1,
    width = 0.5,
    posDecades = 4
)

plotScaleTransformedChannel(
    ff,
    channel = "CD3",
    applyTransform = "data",
    transfoType = "logicle",
    negDecades = 1,
    width = 0.5,
    posDecades = 4
)

# run CytoPipeline object first

outputDir <- base::tempdir()


rawDataDir <-
    system.file("extdata", package = "CytoPipeline")
experimentName <- "OMIP021_PeacoQC"
sampleFiles <- 
    file.path(
        rawDataDir, 
        list.files(rawDataDir, pattern = "Donor"))
jsonDir <- system.file("extdata", package = "CytoPipeline")
jsonPath <- file.path(jsonDir, "pipelineParams.json")

pipL2 <- CytoPipeline(
    jsonPath,
    experimentName = experimentName,
    sampleFiles = sampleFiles)

suppressWarnings(execute(
    pipL2,
    rmCache = TRUE,
    path = outputDir))

ff <- CytoPipeline::getCytoPipelineFlowFrame(
pipL2,
path = outputDir,
whichQueue = "scale transform",
objectName = "flowframe_aggregate_obj"
)

plotScaleTransformedChannel(
    ff,
    channel = "FSC-A",
    transfoType = "linear",
    linA = 0.0002,
    linB = -0.5)

plotScaleTransformedChannel(
    ff,
    channel = "Comp-670/30Violet-A",
    transfoType = "logicle",
    negDecades = 1,
    width = 0.5,
    posDecades = 4
)

plotScaleTransformedChannel(
    ff,
    channel = "CD3",
    applyTransform = "data",
    transfoType = "logicle",
    negDecades = 1,
    width = 0.5,
    posDecades = 4
)

Plot a flow frame from a CytoPipeline run

Description

Based on an experiment name, this function will gather the required flowFrame from the CytoPipeline disk cache and display it using the user chosen 1D or 2D view.

Usage

plotSelectedFlowFrame(
  experimentName,
  whichQueue,
  sampleFile,
  flowFrameName,
  path,
  xChannelLabel,
  yChannelLabel,
  useAllCells,
  nDisplayCells,
  useFixedLinearRange,
  linearRange,
  transfoListName = " "
)
plotSelectedFlowFrame(
  experimentName,
  whichQueue,
  sampleFile,
  flowFrameName,
  path,
  xChannelLabel,
  yChannelLabel,
  useAllCells,
  nDisplayCells,
  useFixedLinearRange,
  linearRange,
  transfoListName = " "
)

Arguments

`experimentName`	the experiment name (representing a pipeline run) from which to extract the flow frame
`whichQueue`	"pre-processing" or "scale transform"
`sampleFile`	in case 'whichQueue' is set to 'pre-processing, which sample file to look at. This can be a number or a character. if whichQueue == "scale transform", the sampleFile is ignored if NULL and whichQueue == "pre-processing", the sampleFile is defaulted to the first one belonging to the experiment
`flowFrameName`	the name of the object to fetch (as referenced in the pipeline workflow)
`path`	the root path to look for the CytoPipeline experiment cache
`xChannelLabel`	the label of the channel to be displayed on the x axis: the conventional syntax is : `channelName` + " - " + `channelMarker`
`yChannelLabel`	the label of the channel to be displayed on the y axis: the conventional syntax is : `channelName` + " - " + `channelMarker`
`useAllCells`	if TRUE, no subsampling will be done
`nDisplayCells`	if useAllCells == FALSE, the number of subsampled cells
`useFixedLinearRange`	if TRUE, all channels using a linear scale will use a fixed range set by linearRange
`linearRange`	set for all channels using a linear scale, if useFixedLinearRange == TRUE
`transfoListName`	if not set to " ", the transformation list (as an object name ending with "_obj", as referenced in the pipeline workflow) to be used for for display.

Value

a ggplot object

Examples


# run CytoPipeline object first

outputDir <- base::tempdir()


rawDataDir <-
    system.file("extdata", package = "CytoPipeline")
experimentName <- "OMIP021_PeacoQC"
sampleFiles <- 
    file.path(
        rawDataDir, 
        list.files(rawDataDir, pattern = "Donor"))
jsonDir <- system.file("extdata", package = "CytoPipeline")
jsonPath <- file.path(jsonDir, "pipelineParams.json")

pipL2 <- CytoPipeline(
    jsonPath,
    experimentName = experimentName,
    sampleFiles = sampleFiles)

suppressWarnings(execute(
    pipL2,
    rmCache = TRUE,
    path = outputDir))

plotSelectedFlowFrame(
    experimentName = experimentName,
    whichQueue = "pre-processing",
    sampleFile = 1,
    flowFrameName = "remove_debris_obj",
    path = outputDir,
    xChannelLabel = "FSC-A : NA",
    yChannelLabel = "SSC-A : NA",
    useAllCells = TRUE,
    nDisplayCells = 0,
    useFixedLinearRange = TRUE,
    linearRange = c(-100, 262144))

plotSelectedFlowFrame(
    experimentName = experimentName,
    whichQueue = "pre-processing",
    sampleFile = 1,
    flowFrameName = "remove_debris_obj",
    path = outputDir,
    xChannelLabel = "FSC-A : NA",
    yChannelLabel = "SSC-A : NA",
    useAllCells = FALSE,
    nDisplayCells = 100,
    useFixedLinearRange = FALSE,
    linearRange = NULL)

plotSelectedFlowFrame(
    experimentName = experimentName,
    whichQueue = "pre-processing",
    sampleFile = 1,
    flowFrameName = "remove_debris_obj",
    path = outputDir,
    xChannelLabel = "Comp-670/30Violet-A : BV785 - CD3",
    yChannelLabel = "Comp-780/60Red-A : APCCy7 - CD4",
    useAllCells = TRUE,
    nDisplayCells = 0,
    useFixedLinearRange = FALSE,
    linearRange = NULL,
    transfoListName = "scale_transform_estimate_obj")

# run CytoPipeline object first

outputDir <- base::tempdir()


rawDataDir <-
    system.file("extdata", package = "CytoPipeline")
experimentName <- "OMIP021_PeacoQC"
sampleFiles <- 
    file.path(
        rawDataDir, 
        list.files(rawDataDir, pattern = "Donor"))
jsonDir <- system.file("extdata", package = "CytoPipeline")
jsonPath <- file.path(jsonDir, "pipelineParams.json")

pipL2 <- CytoPipeline(
    jsonPath,
    experimentName = experimentName,
    sampleFiles = sampleFiles)

suppressWarnings(execute(
    pipL2,
    rmCache = TRUE,
    path = outputDir))

plotSelectedFlowFrame(
    experimentName = experimentName,
    whichQueue = "pre-processing",
    sampleFile = 1,
    flowFrameName = "remove_debris_obj",
    path = outputDir,
    xChannelLabel = "FSC-A : NA",
    yChannelLabel = "SSC-A : NA",
    useAllCells = TRUE,
    nDisplayCells = 0,
    useFixedLinearRange = TRUE,
    linearRange = c(-100, 262144))

plotSelectedFlowFrame(
    experimentName = experimentName,
    whichQueue = "pre-processing",
    sampleFile = 1,
    flowFrameName = "remove_debris_obj",
    path = outputDir,
    xChannelLabel = "FSC-A : NA",
    yChannelLabel = "SSC-A : NA",
    useAllCells = FALSE,
    nDisplayCells = 100,
    useFixedLinearRange = FALSE,
    linearRange = NULL)

plotSelectedFlowFrame(
    experimentName = experimentName,
    whichQueue = "pre-processing",
    sampleFile = 1,
    flowFrameName = "remove_debris_obj",
    path = outputDir,
    xChannelLabel = "Comp-670/30Violet-A : BV785 - CD3",
    yChannelLabel = "Comp-780/60Red-A : APCCy7 - CD4",
    useAllCells = TRUE,
    nDisplayCells = 0,
    useFixedLinearRange = FALSE,
    linearRange = NULL,
    transfoListName = "scale_transform_estimate_obj")

Plot a pipeline workflow from a CytoPipeline run

Description

Plot a pipeline workflow from a CytoPipeline run

Usage

plotSelectedWorkflow(experimentName, whichQueue, sampleFile, path = path)
plotSelectedWorkflow(experimentName, whichQueue, sampleFile, path = path)

Arguments

`experimentName`	the experiment name (representing a pipeline run) from which to extract the workflow
`whichQueue`	"pre-processing" or "scale transform"
`sampleFile`	in case 'whichQueue' is set to 'pre-processing, which sample file to look at. This can be a number or a character. if whichQueue == "scale transform", the sampleFile is ignored if NULL and whichQueue == "pre-processing", the sampleFile is defaulted to the first one belonging to the experiment
`path`	the root path to look for the CytoPipeline experiment cache

Value

nothing, but displays the plot as a side effect

Examples


# run CytoPipeline object first

outputDir <- base::tempdir()


rawDataDir <-
    system.file("extdata", package = "CytoPipeline")
experimentName <- "OMIP021_PeacoQC"
sampleFiles <- 
    file.path(
        rawDataDir, 
        list.files(rawDataDir, pattern = "Donor"))
jsonDir <- system.file("extdata", package = "CytoPipeline")
jsonPath <- file.path(jsonDir, "pipelineParams.json")

pipL2 <- CytoPipeline(
    jsonPath,
    experimentName = experimentName,
    sampleFiles = sampleFiles)

suppressWarnings(execute(
    pipL2,
    rmCache = TRUE,
    path = outputDir))

plotSelectedWorkflow(
    experimentName = experimentName,
    whichQueue = "pre-processing",
    sampleFile = sampleFiles[1],
    path = outputDir)
    
plotSelectedWorkflow(
    experimentName = experimentName,
    whichQueue = "scale transform",
    sampleFile = NULL,
    path = outputDir)


# run CytoPipeline object first

outputDir <- base::tempdir()


rawDataDir <-
    system.file("extdata", package = "CytoPipeline")
experimentName <- "OMIP021_PeacoQC"
sampleFiles <- 
    file.path(
        rawDataDir, 
        list.files(rawDataDir, pattern = "Donor"))
jsonDir <- system.file("extdata", package = "CytoPipeline")
jsonPath <- file.path(jsonDir, "pipelineParams.json")

pipL2 <- CytoPipeline(
    jsonPath,
    experimentName = experimentName,
    sampleFiles = sampleFiles)

suppressWarnings(execute(
    pipL2,
    rmCache = TRUE,
    path = outputDir))

plotSelectedWorkflow(
    experimentName = experimentName,
    whichQueue = "pre-processing",
    sampleFile = sampleFiles[1],
    path = outputDir)
    
plotSelectedWorkflow(
    experimentName = experimentName,
    whichQueue = "scale transform",
    sampleFile = NULL,
    path = outputDir)

interactive display and modification of scale transform list

Description

this application allows the user to visualize a scale transformation list, possibly amending it channel after channel, and save the results on disk. The needed input tranformation list and flow frame for visualization needs to be read from a CytoPipeline experiments stored in cache.

Usage

ScaleTransformApp(dir = ".")
ScaleTransformApp(dir = ".")

Arguments

dir

the root directory into which the engine will look for existing CytoPipeline experiments

Value

no return value

Examples


# run CytoPipeline object first

outputDir <- base::tempdir()


rawDataDir <-
    system.file("extdata", package = "CytoPipeline")
experimentName <- "OMIP021_PeacoQC"
sampleFiles <- 
    file.path(rawDataDir, list.files(rawDataDir, pattern = "Donor"))
jsonDir <- system.file("extdata", package = "CytoPipeline")
jsonPath <- file.path(jsonDir, "pipelineParams.json")

pipL2 <- 
    CytoPipeline(
        jsonPath,
        experimentName = experimentName,
        sampleFiles = sampleFiles)

suppressWarnings(execute(
    pipL2,
    rmCache = TRUE,
    path = outputDir))

# run shiny app

if (interactive())
    ScaleTransformApp(dir = outputDir)                     

# run CytoPipeline object first

outputDir <- base::tempdir()


rawDataDir <-
    system.file("extdata", package = "CytoPipeline")
experimentName <- "OMIP021_PeacoQC"
sampleFiles <- 
    file.path(rawDataDir, list.files(rawDataDir, pattern = "Donor"))
jsonDir <- system.file("extdata", package = "CytoPipeline")
jsonPath <- file.path(jsonDir, "pipelineParams.json")

pipL2 <- 
    CytoPipeline(
        jsonPath,
        experimentName = experimentName,
        sampleFiles = sampleFiles)

suppressWarnings(execute(
    pipL2,
    rmCache = TRUE,
    path = outputDir))

# run shiny app

if (interactive())
    ScaleTransformApp(dir = outputDir)

Package 'CytoPipelineGUI'

Help Index

interactive visualization of flow cytometry data analysis pipeline objects stored in cache

Description

Usage

Arguments

Value

Examples

Plot the difference plot between two flow frames from a CytoPipeline run

Description

Usage

Arguments

Value

Examples

Plot a flow frame in 1D with explicit user given scale transform

Description

Usage

Arguments

Value

Examples

Plot a flow frame from a CytoPipeline run

Description

Usage

Arguments

Value

Examples

Plot a pipeline workflow from a CytoPipeline run

Description

Usage

Arguments

Value

Examples

interactive display and modification of scale transform list

Description

Usage

Arguments

Value

Examples