findFC  R Documentation 
Find the appropriate Fold Change vectors for simulation that will be use in classic differential expression case.
findFC(SCdat, index, sd.range = c(1, 3), N = 4, overExpressionProb = 0.5, plot.FC = FALSE, condition = "condition")
SCdat 
An object of class 
index 
Reasonable set of genes for simulation 
sd.range 
Numeric vector of length two which describes the interval (lower, upper) of standard deviations of fold changes to randomly select. 
N 
Integer value for the number of bins to divide range of fold changes for calculating standard deviations 
overExpressionProb 
Numeric value between 0 and 1 which describes the ratio of over to under expression values to sample. 
plot.FC 
Logical indicating whether or not to plot the observed and simulated log2 fold changes. 
condition 
A character object that contains the name of the column in

This code is a modified version of Sam Younkin's simulate FC function. Major things that were changed are (1) standard deviations are calculated only on the nonzeroes, (2) the sampling of FCs is uniform on the log scale instead of the raw scale, and (3) the binning is done by quantiles instead of evenly spaced along the average expression values.
FC.vec Return Fold Change Vectors
Korthauer KD, Chu LF, Newton MA, Li Y, Thomson J, Stewart R, Kendziorski C. A statistical approach for identifying differential distributions in singlecell RNAseq experiments. Genome Biology. 2016 Oct 25;17(1):222. https://genomebiology.biomedcentral.com/articles/10.1186/s130590161077y
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