View source: R/summaryAnalysis.R
addnorm | R Documentation |
Produces a normalized fluorescence column 'normed'. Expects the 'FL1.A_bs' column to exist or a column to be specified. Has three different methods, version 1 and version 2, described in the script
addnorm( frame, factor_in = c("strain", "treatment"), method = 1, column = "FL3.Amean_bs" )
frame |
|
factor_in |
|
method |
which normalization method to use, 1, 2 or 3. |
column |
|
Method 1, the default normalization method, takes the highest point in each dataset grouped by 'factor_in' and normalizes all values in the group by this point. This method is default because it works regardless of whether the data is a time series. Method 2 finds the mean value of all time points with time values less than 0 for each group and normalizes each group by this respective value. Requires a time series with negative time values to work. Method 3 fits a linear model to the pre-zero time points for each groups, infers the y-intercept, and normalizes using this intercept. Method 3 also requires a time series with negative time values to work.
data frame
containing the additional normalized variable
dat <- read.flowSet(path=system.file("extdata", "tc_example", package = "flowTime"), alter.names = TRUE) annotation <- read.csv(system.file("extdata", "tc_example.csv", package = "flowTime")) adat <- annotateFlowSet(dat, annotation) loadGates(gatesFile = 'C6Gates') dat_sum <- summarizeFlow(adat, ploidy = "diploid", only = "singlets", channel = "FL1.A") dat_sum <- addnorm(dat_sum, c("strain", "treatment"), method = 1, column = "FL1.Amean")
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