normalizeRawIntDen: A function to normalize calcium-sensitivie dye data
In FafferMcgee/calcium-analysis:
Description
Usage
Arguments
Details
Examples
View source: R/normalizeRawIntDen.R
Description
This function will take the data obtained from ImageJ time-series and normalize them to each ROI.
It cleans up the data as well by removing the time column and rawIntDen column obtained from the ImageJ csv.
It also renames the columns from IntDenx to Cell x.
Usage
1
normalizeRawIntDen(rawIntDen)
Arguments
rawIntDen
Dataframe of raw integrated density data from Imagej
Details
It sets the maximum intensity in the time series to 1, and the minimum to 0.
This allows the ROI's analyzed to be compared to one another.
The output of the function should be stored as a variable.
There are two outputs for this function:
One is a standard wide-format that is easy to look at manually.
The other is a 'long' format where the intensity data has been gathered under a key for the cell/ROI being analyzed.
Normalization method: (x-min(x)) / (max(x)-min(x)
Examples
1
normCellData <- normalizeRawIntDen(rawIntData)
FafferMcgee/calcium-analysis documentation built on Sept. 3, 2020, 12:07 a.m.
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Description Usage Arguments Details Examples
View source: R/normalizeRawIntDen.R
Description
This function will take the data obtained from ImageJ time-series and normalize them to each ROI. It cleans up the data as well by removing the time column and rawIntDen column obtained from the ImageJ csv. It also renames the columns from IntDenx to Cell x.
Usage
1 | normalizeRawIntDen(rawIntDen)
|
Arguments
rawIntDen |
Dataframe of raw integrated density data from Imagej |
Details
It sets the maximum intensity in the time series to 1, and the minimum to 0. This allows the ROI's analyzed to be compared to one another.
The output of the function should be stored as a variable. There are two outputs for this function: One is a standard wide-format that is easy to look at manually. The other is a 'long' format where the intensity data has been gathered under a key for the cell/ROI being analyzed.
Normalization method: (x-min(x)) / (max(x)-min(x)
Examples
1 | normCellData <- normalizeRawIntDen(rawIntData)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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