cc.analysis: pHluorin Calibration Curve Analysis

In ctriandafillou/flownalysis: Analysis of Yeast Protein Induction and pH by Flow Cytometry

Description

This function takes raw data from a calibration curve experiment (yeast expressing pHluorin, flow cytometry data) and does all processing steps to construct a calibration curve that maps fluorescence ratio to pH. Takes *raw* (untransformed) FITC and BV510 channels as inputs.

Usage

cc.analysis(subset, background, id, inputs = FALSE, buffer.values = FALSE,
  xmin = 4.9, xmax = 8.6, FITC.thresh = 800, BV.thresh = 800,
  start.list = list(a = 0.5, b = 2, c = 7, d = 0.25), return.plot = TRUE)

Arguments

subset	The dataframe containing the raw calibration curve data. Identifier column should be called 'exp' and formatted as 'cc_pH.fcs'
background	The dataframe containing the raw background data. Identifier column should be called 'exp' and formatted as 'experiment_strain_background' with background being either 'buffer' or 'media'
id	Name/date of experiment, will end up as part of the cc function name so use plaintext characters and no dashes
inputs	A list of column entries that were used during data collection, default is FALSE (inferred from filenames)
buffer.values	A list of buffer values for that day, default is FALSE (inferred from filenames)
xmin	minimum pH predicted (depends on range of buffer values used)
xmax	maximum pH predicted (depends on range of buffer values used)
FITC.thresh	Value that untransformed FITC.A (area) signal must exceed; default is 800
BV.thresh	Value that untransformed BV510.A (area) signal must exceed; default is 800
start.list	Edit the starting fitting parameters; default is list(a=.5, b=2, c=7, d=0.25) (keep this form but change numbers)
return.plot	Boolean, whether or not to create a plot of the resulting calibration curve. Default is TRUE

Details

NEW as of 01-2019: now the resulting conversion function can do adaptive background subtraction

WARNING proper background subtraction only achieved when the data are grouped first (see examples)

Value

convert.to.pH function, plot of calibration curve, analysis of fit quality

Examples

# Given a dataframe 'df' that contains multiple samples with different backgrounds
# background is specified in the column 'recovery'
processed_df <- df %>%
group_by(recovery) %>%
mutate(pH = convert.to.pH(channel1, channel2, media.type = recovery))

ctriandafillou/flownalysis documentation built on Sept. 7, 2020, 1:48 a.m.