Benchmarks for https://stackoverflow.com/q/48607092/1270695

SO48607092.R

library(tidyverse)
library(data.table)
library(microbenchmark)

set.seed(1)
s <- sample(5, 10000, TRUE)
Sample <- rep(seq_along(s), s)
df <- data.frame(Sample, 
                 motif = sample(LETTERS[1:10], length(Sample), TRUE),
                 chromosome = sample(2, length(Sample), TRUE))

myfun <- function() {
    df %>%
      mutate_at(c("motif", "chromosome"), factor) %>%
      mutate(value = 1) %>%
      distinct() %>%
      mutate(key = interaction(motif, chromosome)) %>%
      select(-motif, -chromosome) %>%
      spread(key, value, fill = 0, drop = FALSE)
}
    
florianfun <- function() {
  df  %>% 
    mutate(value=1) %>% 
    complete(motif,chromosome,Sample,fill=list(value=0)) %>%
    mutate(key=paste0(motif,',chr',chromosome)) %>%
    group_by(Sample,key) %>%
    summarize(value = sum(value)) %>%
    spread(key,value)
}

cols <- c("motif", "chromosome")
dtfun <- function() {
  as.data.table(df)[, (cols) := lapply(.SD, factor), .SDcols = cols][
    , dcast(unique(.SD)[, value := 1L], Sample ~ motif + chromosome, value.var = "value", fill = 0L, drop = FALSE)]
}

res <- microbenchmark(myfun(), dtfun(), florianfun(), times = 20)
res
# Unit: milliseconds
#          expr       min        lq      mean    median        uq       max neval
#       myfun()  67.31364  68.33951  71.37471  69.33770  72.01097  84.06912    20
#       dtfun()  19.86292  20.16175  21.23593  20.34515  20.79610  28.40097    20
#  florianfun() 510.52688 517.95171 532.06350 524.14986 534.53571 609.94733    20
autoplot(res)