Package 'RTCA' reference manual

Title:	Open-source toolkit to analyse data from xCELLigence System (RTCA)
Description:	Import, analyze and visualize data from Roche(R) xCELLigence RTCA systems. The package imports real-time cell electrical impedance data into R. As an alternative to commercial software shipped along the system, the Bioconductor package RTCA provides several unique transformation (normalization) strategies and various visualization tools.
Authors:	Jitao David Zhang
Maintainer:	Jitao David Zhang <[email protected]>
License:	LGPL-3
Version:	1.59.0
Built:	2024-10-31 04:28:06 UTC
Source:	https://github.com/bioc/RTCA

Auxilliary functions for experiments with microtitre plates

Description

Functions to manipulate indices or names of microtitre plates

Usage

alphaNames(row = 8, column = 12, order=c("column","row"))
repairAlphaName(x)
alphaNames2Pos(x)
rowcol2pos(row = 1, column=1, plateFormat=c("96","384"))
alphaNames(row = 8, column = 12, order=c("column","row"))
repairAlphaName(x)
alphaNames2Pos(x)
rowcol2pos(row = 1, column=1, plateFormat=c("96","384"))

Arguments

`row`	integer, row index, 1,...,8 for 96-well plates
`column`	integer, column index, 1,...,12 for 96-well plates
`x`	character, Well alpha name, in the form of [A-Z][0-9][0-9], like 'A01'
`order`	character, should the alpha names returned in a row-first or column-first order?
`plateFormat`	integer, the microtitre format, either 96 or 384

Details

alphaNames returns so-called alpha well names in the form of [A-H][0-9][0-9] (i.e., A01, C03, D11, H12) for microtitre plates. The order of returned alphaNames is controlled by the option order, which can be set either as col or row

repairAlphaName attempts to fix incomplete alpha well names. Now it is mainly used to fix well names missing the leading 0 of numeric index, like A1.

alphaName2Pos returns the row and column number of the given alpha well name, in the form of two-column data frame with row and col as colnames.

rowcol2pos returns the row-wise position index of given row and column index.

Value

See details

Author(s)

Jitao David Zhang [email protected]

Examples

wells <- alphaNames()

repairAlphaName("A1")

alphaNames2Pos(c("A01","B02","C03","H12"))

rowcol2pos(3,1)
wells <- alphaNames()

repairAlphaName("A1")

alphaNames2Pos(c("A01","B02","C03","H12"))

rowcol2pos(3,1)

Combine a list of RTCA objects

Description

Combine a list of RTCA objects

Usage

combineRTCA(list)
combineRTCA(list)

Arguments

list

A list of RTCA objects

Details

The current implementation requires all the objects have exactly the same time-points recorded (or at least of same length).

The combined RTCA object has an obligatory column in the phenoData ‘Plate’ (upper-case!), which matches the names of the RTCA list. When the list has no names, the ‘Plate’ field is filled with integer index starting from 1.

Value

A new RTCA object

Note

Special attention should be given to the cases where the list parameter partially has names. In this case all items without name will be assigned to a ‘Plate’ field of empty string (“”). Therefore it is advised either to assign names to all items of the list, or leave them all off.

Author(s)

Jitao David Zhang [email protected]

Examples

## An artificial example
require(RTCA)
  
ofile <- system.file("/extdata/testOutput.csv", package="RTCA")
x <- parseRTCA(ofile)

xSub1 <- x[,1:3]
xSub2 <- x[,4:ncol(x)]
xComb <- combineRTCA(list(sub1=xSub1, sub2=xSub2))
identical(exprs(x), exprs(xComb))
pData(xComb)$Plate

## in case of nameless list
pData(combineRTCA(list(xSub1, xSub2)))$Plate

## partial names
pData(combineRTCA(list(a=xSub1, xSub2)))$Plate
## An artificial example
require(RTCA)
  
ofile <- system.file("/extdata/testOutput.csv", package="RTCA")
x <- parseRTCA(ofile)

xSub1 <- x[,1:3]
xSub2 <- x[,4:ncol(x)]
xComb <- combineRTCA(list(sub1=xSub1, sub2=xSub2))
identical(exprs(x), exprs(xComb))
pData(xComb)$Plate

## in case of nameless list
pData(combineRTCA(list(xSub1, xSub2)))$Plate

## partial names
pData(combineRTCA(list(a=xSub1, xSub2)))$Plate

PLOT CONTROL WELLS IN RTCA DATA

Description

A convenience function to plot sample wells with control wells on an E-plate in RTCA system. To use the function the phenoData field of the RTCA object must contain a field named “GeneSymbol”.

Usage

controlView(rtca, genesymbol = c("Allstar", "COPB2", "GFP", "mock", "PLK1", "WEE1"), cols, ylim, smooth = FALSE, group = TRUE, ylab = "Normalized cell index", xlab = "Time interval (hour)", drawsd = TRUE, normline = TRUE, ncol = 1, legendpos = "topleft", pData.column="GeneSymbol",...)
controlView(rtca, genesymbol = c("Allstar", "COPB2", "GFP", "mock", "PLK1", "WEE1"), cols, ylim, smooth = FALSE, group = TRUE, ylab = "Normalized cell index", xlab = "Time interval (hour)", drawsd = TRUE, normline = TRUE, ncol = 1, legendpos = "topleft", pData.column="GeneSymbol",...)

Arguments

`rtca`	An object of `RTCA`.To use the function, the phenoData must contain a column which name is specified by the `pData.column` parameter.
`genesymbol`	character, gene symbols to be plotted.
`cols`	character, colors used by the provided gene symbols
`ylim`	y-axis lim
`smooth`	logical, whether the `RTCA` object should be smoothed before plotting
`group`	logical. If ‘group’ is set to `TRUE`, wells with the same GeneSymbol will be summarized and plotted. For instance, these could be biological replicates. Otherwise each well is plotted separatedly
`ylab`	y axis label
`xlab`	x axis label
`drawsd`	logical, should the error bar be drawn to represent standard deviation?
`normline`	logical, should the base-time indicated by a line? See `ratioTransform` for the concept of the base-time
`ncol`	integer, legend column number
`legendpos`	character, legend position
`pData.column`	The column which the `genesymbol` parameter will be matched with
`...`	other parameters passed to the `plot` function

Details

The function is often called to draw sample and control in one plot.

Value

NULL, the function is called for its side effect

Author(s)

Jitao David Zhang [email protected]

Examples

require(RTCA)
  
ofile <- system.file("extdata/testOutput.csv", package="RTCA")
pfile <- system.file("extdata/testOutputPhenoData.csv", package="RTCA")

pData <- read.csv(pfile, sep="\t", row.names="Well")
metaData <- data.frame(labelDescription=c(
"Rack number",
"siRNA catalogue number",
"siRNA gene symbol",
"siRNA EntrezGene ID",
"siRNA targeting accession"
))

phData <- new("AnnotatedDataFrame", data=pData, varMetadata=metaData)
x <- parseRTCA(ofile, phenoData=phData)

controlView(x, genesymbol=c("mock","COPB2","PLK1"),ylim=c(0,2))
require(RTCA)
  
ofile <- system.file("extdata/testOutput.csv", package="RTCA")
pfile <- system.file("extdata/testOutputPhenoData.csv", package="RTCA")

pData <- read.csv(pfile, sep="\t", row.names="Well")
metaData <- data.frame(labelDescription=c(
"Rack number",
"siRNA catalogue number",
"siRNA gene symbol",
"siRNA EntrezGene ID",
"siRNA targeting accession"
))

phData <- new("AnnotatedDataFrame", data=pData, varMetadata=metaData)
x <- parseRTCA(ofile, phenoData=phData)

controlView(x, genesymbol=c("mock","COPB2","PLK1"),ylim=c(0,2))

DERIVATIVE TRANSFORM OF RTCA OBJECT

Description

Derivative transform of RTCA object, returning the change rate of cell impedance

Usage

derivativeTransform(object)
derivativeTransform(object)

Arguments

object

An object of RTCA

Details

The first derivative of the cell impedance curve measured by RTCA. The derivative of the last time point is estimated by that of the next to last point.

Value

An RTCA object populated with derivative values

Author(s)

Jitao David Zhang [email protected]

Examples

require(RTCA)
  
ofile <- system.file("/extdata/testOutput.csv", package="RTCA")
x <- parseRTCA(ofile)

xDeriv <- derivativeTransform(x)
require(RTCA)
  
ofile <- system.file("/extdata/testOutput.csv", package="RTCA")
x <- parseRTCA(ofile)

xDeriv <- derivativeTransform(x)

FACTOR UNITILITIES

Description

The functions implement easy interface to certain tasks of factor. See datails for explaination

Usage

factor2numeric(x)
relevels(x, refs)
factor2numeric(x)
relevels(x, refs)

Arguments

`x`	A vector of factor
`refs`	A vector of character, reference vector to give the orderof levels

Details

relevels re-arrange the order of levels by the given character refs. Alternatively user could use factor(...,levels=refs) to achieve a similar effect, however the relevels enables also partial list. The missing levels in refs will be ordered to the last.

factor2numeric converts factor of numerics into their numeric form.

Value

A vector of factor

Author(s)

Jitao David Zhang [email protected]

Examples

## factor2numeric
numFac <- factor(c(3.5, 2.5, 2.5,3.5, 1))
numFac
levels(numFac)

factor2numeric(numFac)
class(factor2numeric(numFac))

## relevels
relevels(numFac, c("3.5", "1", "2.5"))
relevels(numFac, c("3.5", "2.5"))
## factor2numeric
numFac <- factor(c(3.5, 2.5, 2.5,3.5, 1))
numFac
levels(numFac)

factor2numeric(numFac)
class(factor2numeric(numFac))

## relevels
relevels(numFac, c("3.5", "1", "2.5"))
relevels(numFac, c("3.5", "2.5"))

TRANSFORM RTCA DATA WITH INTERPOLATION

Description

Interpolate RTCA data

Usage

interpolationTransform(object, interval=0.01, method=c("linear","constant","fmm","periodic","natural", "monoH.FC"))
interpolationTransform(object, interval=0.01, method=c("linear","constant","fmm","periodic","natural", "monoH.FC"))

Arguments

`object`	An `RTCA` object
`...`	other parameters, `interval` and `method` are implemented, see below
`interval`	numeric, the interval between interpolated points, set to 0.01 by default
`method`	character, specifying the method for interpolation, “linear” by default (for linear interpolation). Allowed options are: “linear” and “constant” for `approx` interpolation, and “fmm”, “periodic”, “natural” and “monoH.FC” for cubic spline interpolation

Details

Since most RTCA experiements record the experiments in the irregular time-series, sometimes however it is desired to have regular intervals. interpolationTransform interpolate between data points to estimate results of regular intervals.

Two classes of interpolations are supported by now: linear (using approx) and cubic spline (spline) interpolation. By default linear interpolation is used.

Value

An interpolated object of RTCA.

Author(s)

Jitao David Zhang [email protected]

Examples

require(RTCA)
  
ofile <- system.file("/extdata/testOutput.csv", package="RTCA")
x <- parseRTCA(ofile)

xInter <- interpolationTransform(x)
require(RTCA)
  
ofile <- system.file("/extdata/testOutput.csv", package="RTCA")
x <- parseRTCA(ofile)

xInter <- interpolationTransform(x)

GET INDEX FOR NEAREST TIME

Description

Get index for the nearest time point to the given one. Called internally in many time-point related functions.

Usage

nearestTimeIndex(rtca, time)
nearestTimeIndex(rtca, time)

Arguments

`rtca`	An object of `RTCA`
`time`	numeric, a time point

Details

The function finds the time point with minimum absolute difference to the given time and returns its index.

Value

An integer, the index of the nearest time point

Author(s)

Jitao David Zhang [email protected]

Examples

require(RTCA)
  
ofile <- system.file("/extdata/testOutput.csv", package="RTCA")
x <- parseRTCA(ofile)

x
xIndex <- nearestTimeIndex(x, 25)
timepoints(x)[xIndex]
require(RTCA)
  
ofile <- system.file("/extdata/testOutput.csv", package="RTCA")
x <- parseRTCA(ofile)

x
xIndex <- nearestTimeIndex(x, 25)
timepoints(x)[xIndex]

PARSE RTCA OUTPUT FILE

Description

The function parses RTCA output file into RTCA object

Usage

parseRTCA(file, dec = ".", phenoData, maskWell, ...)
parseRTCA(file, dec = ".", phenoData, maskWell, ...)

Arguments

`file`	character, name of the RTCA output file
`dec`	decimal sign of the file
`phenoData`	phenoData
`maskWell`	character, either names or regular expression pattern(s) for well(s) to mask
`...`	other parameters passed to `read.table`

Details

A csv-like format file can be exported from the RTCA device, which can be fed into this function to set up an instance of RTCA object.

In the /extdata/ directory of the package, such a file is provided as an example. The first line contains the experiment ID, which is followed by a matrix of recorded data in the tabular form. The first and second column records the time-interval in the unit of hour and hour-minute-second format respectively. The rest columns then record the read-out (‘Cell-Index’, or ‘CI’) of the device, with each well a role.

phenoData allows user to annotate the wells.Its usage mimicks the ExpressionSet object in the Biobase package.

maskWell allows to mask wells in case, for example, they are known to be contaminated. The values can be either a vector of well names, or a regular expression pattern for wells to be masked. To learn regular expression patterns see grep.

Value

An object of RTCA-class

Author(s)

Jitao David Zhang [email protected]

References

http://www.roche-applied-science.com/proddata/gpip/3_8_9_1_1_1.html

Examples

require(RTCA)
  
ofile <- system.file("extdata/testOutput.csv", package="RTCA")
pfile <- system.file("extdata/testOutputPhenoData.csv", package="RTCA")

pData <- read.csv(pfile, sep="\t", row.names="Well")
metaData <- data.frame(labelDescription=c(
"Rack number",
"siRNA catalogue number",
"siRNA gene symbol",
"siRNA EntrezGene ID",
"siRNA targeting accession"
))

phData <- new("AnnotatedDataFrame", data=pData, varMetadata=metaData)
x <- parseRTCA(ofile, phenoData=phData)

print(x)

## mask wells, e.g. due to unusual values
x.skip <- parseRTCA(ofile, phenoData=phData, maskWell=c("D09"))
x.skip.multiWells <- parseRTCA(ofile, phenoData=phData, maskWell=c("A01", "B01",
"C02"))
## skip the last row
x.skip.pattern <- parseRTCA(ofile, phenoData=phData,
maskWell=c("H[0-9]{2}"))

## check the number of masked wells
noMasked <- function(x) sum(apply(x, 2, function(x) all(is.na(x))))
noMasked(exprs(x))
noMasked(exprs(x.skip))
noMasked(exprs(x.skip.multiWells))
noMasked(exprs(x.skip.pattern))
require(RTCA)
  
ofile <- system.file("extdata/testOutput.csv", package="RTCA")
pfile <- system.file("extdata/testOutputPhenoData.csv", package="RTCA")

pData <- read.csv(pfile, sep="\t", row.names="Well")
metaData <- data.frame(labelDescription=c(
"Rack number",
"siRNA catalogue number",
"siRNA gene symbol",
"siRNA EntrezGene ID",
"siRNA targeting accession"
))

phData <- new("AnnotatedDataFrame", data=pData, varMetadata=metaData)
x <- parseRTCA(ofile, phenoData=phData)

print(x)

## mask wells, e.g. due to unusual values
x.skip <- parseRTCA(ofile, phenoData=phData, maskWell=c("D09"))
x.skip.multiWells <- parseRTCA(ofile, phenoData=phData, maskWell=c("A01", "B01",
"C02"))
## skip the last row
x.skip.pattern <- parseRTCA(ofile, phenoData=phData,
maskWell=c("H[0-9]{2}"))

## check the number of masked wells
noMasked <- function(x) sum(apply(x, 2, function(x) all(is.na(x))))
noMasked(exprs(x))
noMasked(exprs(x.skip))
noMasked(exprs(x.skip.multiWells))
noMasked(exprs(x.skip.pattern))

PLATE VIEW OF RTCA DATA

Description

Plots a E-plate in RTCA assays in one plot to convey an overview of the plate

Usage

plateView(rtca, ylim, titles,...)
plateView(rtca, ylim, titles,...)

Arguments

`rtca`	An object of `RTCA`
`ylim`	ylab lim
`titles`	Titles of sub-figures representing each well. If missing, the function seeks whether a Well column is available in the pData of the RTCA object, and if so, its value will be used. If not, the sample names (by `sampleNames` function) will be used as titles.
`...`	Other parameters passed to the `plot` function. Currently options `col`, `lty` and `lwd` are supported. See details below.

Details

For now the function only supports the visualization of a 96-well E-plate.

The plate view plot draws lines indicating cell index (or its transformations) in a birdview. When ... are not specified, default color, line style and width are used. col,lty and lwd can be a vector, and if needed they will be expanded to have the same length as wells.

Value

NULL, the function is called for the side effect

Author(s)

Jitao David Zhang [email protected]

Examples

require(RTCA)
  
ofile <- system.file("extdata/testOutput.csv", package="RTCA")
rtca <- parseRTCA(ofile)

## Not run automatically, because of 'margin too large'
## plateView(rtca)
## plateView(rtca, lty=2)
## plateView(rtca, col=rep(1:8, each=12))

rtca.skip <- parseRTCA(ofile, maskWell="H[0-9]{2}")
## plateView(rtca.skip)
require(RTCA)
  
ofile <- system.file("extdata/testOutput.csv", package="RTCA")
rtca <- parseRTCA(ofile)

## Not run automatically, because of 'margin too large'
## plateView(rtca)
## plateView(rtca, lty=2)
## plateView(rtca, col=rep(1:8, each=12))

rtca.skip <- parseRTCA(ofile, maskWell="H[0-9]{2}")
## plateView(rtca.skip)

PLOT GRID EFFECT OF RTCA

Description

Plot the mean and deviation of rows/columns of a RTCA E-plate, to provide hints of potential row/column effect of the plate

Usage

plotGridEffect(rtca, mode = c("column", "row"), xlab = "time point",
ylab = "readout", legend = TRUE, col, ...)
plotGridEffect(rtca, mode = c("column", "row"), xlab = "time point",
ylab = "readout", legend = TRUE, col, ...)

Arguments

`rtca`	An object of `RTCA`
`mode`	character, either “column” or “row”, to choose which effect to depict
`xlab`	x-axis label
`ylab`	y-axis label
`legend`	logical, whether the legend should be added
`col`	Color of the curves
`...`	Further parameters passed to `plot` function

Details

The error bars depicts the standard deviations

Value

NULL, the funciton is called for its side effect

Author(s)

Jitao David Zhang

Examples

require(RTCA)
  
ofile <- system.file("extdata/testOutput.csv", package="RTCA")
x <- parseRTCA(ofile)
plotGridEffect(x)
require(RTCA)
  
ofile <- system.file("extdata/testOutput.csv", package="RTCA")
x <- parseRTCA(ofile)
plotGridEffect(x)

RATIO TRANSFORMATION OF RTCA DATA

Description

Performs ratio transformation (normalisation) of RTCA data, as recommended by the producer Roche.

Usage

ratioTransform(object, time)
ratioTransform(object, time)

Arguments

`object`	An object of `RTCA`
`time`	numeric, the time point used to normalize the whole series of data

Details

The xCelligence software provided by Roche performs ratio transform implicitly by dividing the time-series impedance measurement by the value of a selected time point (so-called 'base-time'), for instance 5 hours after compound transfection, in each cell. The aim of this transformation was to scale (normalize) the data of different wells, since the normalized values of all wells are uniformly 1 at the base-time.

However, this method is vulnerable to arbitrary selection of the time point chosen to normalize. It may be helpful to try several base-time values before comparing normalized results.

See derivativeTransform and rgrTransform for other normalization (scaling) possibilities.

Value

An object of RTCA, populated with normalized value. The normalized values of all wells are uniformly 1 at the base-time.

Author(s)

Jitao David Zhang [email protected]

Examples

require(RTCA)
  
ofile <- system.file("/extdata/testOutput.csv", package="RTCA")
x <- parseRTCA(ofile)

xNorm <- ratioTransform(x, 35)
require(RTCA)
  
ofile <- system.file("/extdata/testOutput.csv", package="RTCA")
x <- parseRTCA(ofile)

xNorm <- ratioTransform(x, 35)

TRANSFORM RTCA DATA INTO RELATIVE GROWTH RATE

Description

Transform RTCA data into relative growth rate

Usage

rgrTransform(object, smooth)
rgrTransform(object, smooth)

Arguments

`object`	An object of `RTCA`
`smooth`	logical, should the object be smooth transformed after the `rgrTransform`? Set to `TRUE` by default

Details

TODO: relative growth rate

Value

An object of RTCA populated with relative growth rate instead of input data

Author(s)

Jitao David Zhang <[email protected]>

References

TODO: reference

Examples

require(RTCA)
  
ofile <- system.file("/extdata/testOutput.csv", package="RTCA")
x <- parseRTCA(ofile)

xRgr <- rgrTransform(x)
require(RTCA)
  
ofile <- system.file("/extdata/testOutput.csv", package="RTCA")
x <- parseRTCA(ofile)

xRgr <- rgrTransform(x)

Class "RTCA"

Description

RTCA object

Objects from the Class

Objects can be created by calls of the form new("RTCA", assayData, phenoData, featureData, experimentData, annotation, exprs, ...). However, it is more common to be constructed by parseRTCA function by reading in RTCA output data directly.

Slots

expID:: Object of class "character", experiment ID
timeline:: Object of class "RTCAtimeline", recording action track along the time line
assayData:: Object of class "AssayData", assay data inherited from ExpressionSet-class
phenoData:: Object of class "AnnotatedDataFrame", pheno data of the assay, annotating the wells
featureData:: Object of class "AnnotatedDataFrame", feature data of the assay, preserved for time-line recording by the package
experimentData:: Object of class "MIAME", idle
annotation:: Object of class "character", idle
.__classVersion__:: Object of class "Versions",idle

Extends

Class ExpressionSet-class, directly. Class eSet-class, by class "ExpressionSet", distance 2. Class VersionedBiobase-class, by class "ExpressionSet", distance 3. Class Versioned-class, by class "ExpressionSet", distance 4.

Methods

addAction: signature(object = "RTCA", time = "numeric", action = "character"): add action at the specified time, passed to the RTCAtimeline slot
getAction: signature(object = "RTCA", time = "numeric"): get action at the specified time, passed to the RTCAtimeline slot
plotRTCA: signature(x = "RTCA"): plot RTCA
rmAction: signature(object = "RTCA", time = "numeric"): remove action at the specified time, passed to the RTCAtimeline slot
show: signature(object = "RTCA"): print method
expID: codesignature(object = "RTCA"): get Experiment ID
expID<-: codesignature(object = "RTCA", value = "ANY"): set Experiment ID
time: signature(x = "RTCA"): deprecated
timeline: signature(object = "RTCA"): get the RTCAtimeline slot
timeline<-: signature(object = "RTCA"): assign the RTCAtimeline slot
timepoints: signature(object = "RTCA"): get the recording time points in a vector
timepoints<-: signature(object = "RTCA"): assign the recording time points
updateAction: signature(object = "RTCA", time = "numeric", action = "character"): update the action at the specified time, passed to the RTCAtimeline slot
plot: signature(x = "RTCA", y): plot the RTCA running plot with matplot. y is interpretated as the indices of the columns to be plotted, and will be expanded to all the columns in case it is missing.

Author(s)

Jitao David Zhang [email protected]

References

1: https://www.roche-applied-science.com/sis/xcelligence/index.jsp?id=xcect_000000 introduces xCelligence system.
2: http://www.roche-applied-science.com/proddata/gpip/3_8_9_1_1_1.html for brief introduction into RTCA

Examples

new("RTCA", expID="testExp01")
new("RTCA", expID="testExp01")

Class "RTCAtimeline"

Description

Time line of actions performed by the xCelligence device, supporting CRUD manipulations (create, read, update and delete).

Objects from the Class

Objects can be created by calls of the form new("RTCAtimeline"). However, it is more common to be called implicitly by creating an instance of RTCA object.

Slots

actionTrack:: Object of class "data.frame", records action track in the form of two-column data.frame. The two columns must have the names ‘time’ and ‘action’.
timeUnit:: Object of class "character", recording the unit of time points stored in the actionTrack slot.
startTime:: Object of class "POSIXct", the absolute time when the measurement started (at the time point ‘0’)

Methods

addAction: signature(object = "RTCAtimeline", time = "numeric", action = "character"): add action at the specified time
actionTrack: signature(object = "RTCAtimeline"): get the action track in the form of data.frame
actionTrack<-: signature(object = "RTCAtimeline", value = "data.frame"): assign the action track
getAction: signature(object = "RTCAtimeline", time = "numeric"): get action at the specified time
orderAction: signature(object = "RTCAtimeline"): order the action track by the time
reset: signature(object = "RTCAtimeline"): undo all editing of the object and reset it to the initial state
rmAction: signature(object = "RTCAtimeline", time = "numeric"): remove the action at the specified time
timeUnit: signature(object = "RTCAtimeline"): return the time unit used by the actiont track
timeUnit<-: signature(object = "RTCAtimeline", value = "character"): assign the time unit used by the actiont track
start: signature(object = "RTCAtimeline"): return the starting POSIXct time of the experiment
timeUnit<-: signature(object = "RTCAtimeline", value = "character"): assign the starting POSIXct time of the experiment

Author(s)

Jitao David Zhang [email protected]

References

1: http://www.xcelligence.roche.com/ introduces xCelligence system.
2: http://www.roche-applied-science.com/proddata/gpip/3_8_9_1_1_1.html for brief introduction into RTCA

Examples

tl <- new("RTCAtimeline")
show(tl)
tl <- new("RTCAtimeline")
show(tl)

SLICE RTCA OBJECT WITH TIME

Description

Subset (slice) RTCA object with starting- and ending-time

Usage

sliceRTCA(x, start, end)
sliceRTCA(x, start, end)

Arguments

`x`	An object of `RTCA`
`start`	numeric, start time
`end`	numeric, end time

Details

In case the exact starting- or ending-time is not matched, the nearest time point will be used to subset.

Value

An object of RTCA

Author(s)

Jitao David Zhang [email protected]

Examples

  require(RTCA)
  
  ofile <- system.file("/extdata/testOutput.csv", package="RTCA")
  x <- parseRTCA(ofile)

  subx <- sliceRTCA(x, 20, 50)
require(RTCA)
  
  ofile <- system.file("/extdata/testOutput.csv", package="RTCA")
  x <- parseRTCA(ofile)

  subx <- sliceRTCA(x, 20, 50)

SMOOTH TRANSFORM OF RTCA OBJECT

Description

Smoothing the RTCA cell impedance measurement

Usage

smoothTransform(object, ...)
smoothTransform(object, ...)

Arguments

`object`	An object of `RTCA`
`...`	Parameters passed to `smooth.spline`

Details

smoothTransform smooths the RTCA cell impedance measurement by calling the function smooth.spline. This feature can be useful for visualiation purposes and in conjuction with other transformations.

Value

An RTCA object populated with smoothed values

Note

ratioTransform performs ratio transformation recommended by the machine provider. interpolationTransform for interpolating the RTCA data. derivativeTransform returns cell impedance change rates and rgrTransform calculates relative growth rate.

Author(s)

Jitao David Zhang [email protected]

Examples

require(RTCA)
  
ofile <- system.file("/extdata/testOutput.csv", package="RTCA")
x <- parseRTCA(ofile)

xSmooth <- smoothTransform(x)
require(RTCA)
  
ofile <- system.file("/extdata/testOutput.csv", package="RTCA")
x <- parseRTCA(ofile)

xSmooth <- smoothTransform(x)

Import output files from Spectramax spectrophotometer

Description

Import output files from Spectramax spectrophotometer (plate reader) into the list format compatible with the cellHTS2 package.

Usage

spectramaxImport(file, encoding="latin1")
spectramaxImport(file, encoding="latin1")

Arguments

`file`	A Spectramax file
`encoding`	File character encoding, by default “latin1”

Details

The function imports output files from Spectramax plate reader, with which single-channel cell-based assays could be performed. Such assay includes WST-1 viability assay, which can be used to validate RTCA assay results.

Value

A list of two items: one data frame (no name) and one character vector (txt). The data frame contains following columns:

`well`	Well indices ([A-Z][0-9][0-9] format) on the microtitre plate
`val`	Value of each well

The character vector txt contains a copy of the file contents.

Author(s)

Jitao David Zhang <[email protected]>

Examples

wstFiles <- dir(system.file("extdata", package="RTCA"),
pattern="^WST.*csv$", full.names=TRUE)
spectramaxImport(wstFiles[1])

## NOT RUN
## spectramaxImport also supports multiple files, in which case the
## result is a list of individual lists
spectramaxImport(wstFiles)
## END NOT RUN
wstFiles <- dir(system.file("extdata", package="RTCA"),
pattern="^WST.*csv$", full.names=TRUE)
spectramaxImport(wstFiles[1])

## NOT RUN
## spectramaxImport also supports multiple files, in which case the
## result is a list of individual lists
spectramaxImport(wstFiles)
## END NOT RUN

Package 'RTCA'

Help Index

Auxilliary functions for experiments with microtitre plates

Description

Usage

Arguments

Details

Value

Author(s)

Examples

Combine a list of RTCA objects

Description

Usage

Arguments

Details

Value

Note

Author(s)

Examples

PLOT CONTROL WELLS IN RTCA DATA

Description

Usage

Arguments

Details

Value

Author(s)

See Also

Examples

DERIVATIVE TRANSFORM OF RTCA OBJECT

Description

Usage

Arguments

Details

Value

Author(s)

See Also

Examples

FACTOR UNITILITIES

Description

Usage

Arguments

Details

Value

Author(s)

Examples

TRANSFORM RTCA DATA WITH INTERPOLATION

Description

Usage

Arguments

Details

Value

Author(s)

See Also

Examples

GET INDEX FOR NEAREST TIME

Description

Usage

Arguments

Details

Value

Author(s)

See Also

Examples

PARSE RTCA OUTPUT FILE

Description

Usage

Arguments

Details

Value

Author(s)

References

Examples

PLATE VIEW OF RTCA DATA

Description

Usage

Arguments

Details

Value

Author(s)

See Also