# R/smoothness.r In DeLorean: Estimates Pseudotimes for Single Cell Expression Data

#### Documented in calc.roughnesspermute.df

```#' Calculate the roughness of the vector. The roughness is the RMS
#' of the differences between consecutive points.
#'
#' @param x Values
#'
calc.roughness <- function(x) {
N <- length(x)
stopifnot(N > 0)
if (0 == N) return(0)
S <- sd(x)
if (S == 0) return(0)
sqrt(sum((x[1:(N-1)] - x[2:N])**2) / (N-1)) / S
}

#' Permute a data frame, x. If group.col is given it should name an ordered
#' factor that the order of the permutation should respect.
#'
#' @param .df Data frame
#' @param group.col Name of an ordered factor that the permutation
#'    should respect.
#'
permute.df <- function(.df, group.col=NULL) {
if (is.null(group.col)) {
return(.df[sample(nrow(.df)),])
} else {
stopifnot(is.ordered(.df[,group.col]))
return(
.df
%>% group_by_(as.symbol(group.col))
%>% do(permute.df(.)))
}
}

#' Calculate the roughness of the held out genes given the sample.
#'
#' @param dl de.lorean object
#' @param expr.held.out The expression matrix including the held out genes
#' @param sample.iter Which sample to use
#'
roughness.of.sample <- function(
dl,
expr.held.out=dl\$expr.held.out,
sample.iter=dl\$best.sample)
with(dl, {
tau <- tau.for.sample(dl, sample.iter=sample.iter)
mean(apply(expr.held.out[,order(tau)], 1, calc.roughness))
})

#' Permute cells and test roughness of expression.
#'
#' @param dl de.lorean object
#' @param expr.held.out The expression matrix of the held out genes
#'
permuted.roughness <- function(
dl,
expr.held.out=dl\$expr.held.out)
{
permuted <- permute.df(dl\$cell.map, "capture")
apply(expr.held.out[,permuted\$c], 1, calc.roughness)
}

#' Apply permutation based roughness test to held out genes
#'
#' @param dl de.lorean object
#' @param expr.held.out The expression matrix including the held out genes
#' @param num.perms Number of permutations to test
#'
roughness.of.permutations <- function(
dl,
expr.held.out=dl\$expr.held.out,
num.perms=1000)
{
colMeans(sapply(1:num.perms, function(i) permuted.roughness(dl, expr.held.out)))
}

#' Calculate roughnesses under fit samples and also under random
#' permutations
#'
#' @param dl de.lorean object
#' @param expr.held.out The expression matrix including the held out genes
#' @param num.perms Number of permutations to test
#'
#' @export
#'
roughness.test <- function(
dl,
expr.held.out=dl\$expr.held.out,
num.perms=1000)
within(dl, {
message('Performing roughness test on ', nrow(expr.held.out),
' genes and ', ncol(expr.held.out),
' cells. Using ', num.perms, ' permutations.')
# Combine both types into a dataframe
roughnesses <- rbind(
data.frame(type="pseudotime", sample.iter=sample.iters(dl))
%>% mutate(roughness=Vectorize(
roughness.of.sample,
vectorize.args='sample.iter'
)(
dl,
expr.held.out=expr.held.out,
sample.iter
)),
data.frame(type="permutation",
sample.iter=NA,
roughness=roughness.of.permutations(dl, held.out.expr)))
roughness.test <- t.test(
x=filter(roughnesses, "permutation" == type)\$roughness,
y=filter(roughnesses, "pseudotime"  == type)\$roughness,
alternative="greater")
})

#' Plot results of roughness test
#'
#' @param dl de.lorean object
#'
#' @export
#'
roughnesses.plot <- function(dl) with(dl, (
ggplot(roughnesses, aes(x=roughness,
fill=type, color=type))
+ geom_histogram(aes(y=..density..), position='dodge')
+ geom_rug()
+ geom_vline(
xintercept=filter(roughnesses, dl\$best.sample==sample.iter)\$roughness,
linetype='dashed', color='blue')
))
```

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DeLorean documentation built on May 2, 2019, 9:24 a.m.