nc_ratio_profile: Nuclear to Cytoplasmic Signal Ratio Analysis on Stacked...
In dami82/CellSignalingTools: Analysis of Images for Molecular Biology Applications

Description Usage Arguments Value Author(s) References Examples

Analyze Stacked Signal Profiles (calculated using plotProfile tool of ImageJ or similar software) and determine the nuclear to non-nuclear signal ratio. A plot displaying the signal intensity in the green and the DAPI channels is also displayed.

nc_ratio_profile(profile_tab, 
bckgr_subtr = "baseline", 
mode = "auc", 
condition = "", 
antibody = "Ab - I", 
show_labels = TRUE, 
noise = 0.05)

`profile_tab`	is a data frame containing a X1 column (position along x), an one or more pairs of Gi, Bi columns (signal intensity in the Green channel and Blue channel along x). If profile_tab is not correctly formatted, the functionn will not work correctly.
`bckgr_subtr`	is one of the strings in c("baseline, "confocal""). It is the type of background subtraction that will be employed
`mode`	is one of the strings in c("auc", "mean"). It determines whether the nuclear/cyto signal ratio is calculated based on average signal or area-under-curve.
`condition`	is an optional string that will be used as title of the plot
`antibody`	is a string that will be used as a label for the signal in the green channel
`show_labels`	is a boolean and determines whether displaying extra information on the profile plots
`noise`	is a number in the range 0 to 1 and define the signal threshold to be used for background correction

list of numeric vectors. Each element of the list corresponds to one of the cells analyzed. Each numeric vector includes values for nuclear signal, non-nuclear signal and ratio nucl / non-nucl.

Damiano Fantini

http://www.biotechworld.it/bioinf/2016/03/09/analyzing-fluoresence-microscopy-data-with-r/

data("leio_basal_profile")
data("leio_pq100_profile")

items <- list(leio_basal_profile, leio_pq100_profile)
conditions <- c('CTR','PQ100')
results <- lapply(1:2, (function(n){
  nc_ratio_profile(items[[n]], 
  bckgr_subtr = "baseline", 
  mode = "mean", 
  condition = conditions[n], 
  antibody = "PTEN", 
  show_labels = TRUE, 
  noise = 0.05)
}))