npjc

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npjc

title	author	date	output
2 - normalizing counts	Nicolas Coutin	August 29, 2014	html_document

Generate windowed reference files.

Run bash scripts

npjc

with combined 3-colbed + 4th col. id
```r
library(data.table)

y = data.table(chr=c("Chr1", "Chr1", "Chr1"), start=c(1, 15,1), 
               end=c(4, 18, 55), id=letters[1:3])
setkey(y, chr, start, end)

dt <- foverlaps(y, y, type="any")
```

npjc

library(httr)
library(dplyr)
url <- "https://www.github.com"

# all possible alpha numeric names
allowed_n_letters <- 1:3 # just change this to check others...
possible_paths <- lapply(allowed_n_letters,function(x) {
  combn(letters, x) %>% apply(2, paste0, collapse="")
}) %>% unlist()

npjc

synopsis

I have a large file (too big to read in memory) and I want to generate subsets of the file. The subsets are defined by a column in the file. In other words, I split one file into n files where n = unique values in file column.

use it

library(data.table)
path <- "small.tsv"
split_file(path , col_idx = 4, chunk_size = 1e7, skip = 0)

npjc

# pace to secs...minute:seconds character string to seconds integer
pts <- function(ms = "4:45") {
  tmp <- as.integer(unlist(strsplit(ms, ":", fixed = TRUE)))
  tmp[1]*60 + tmp[2]
}

# seconds to total time in hour:minute:seconds
ttl_time <- function(s) {
  hrs <- floor(s / 3600)
  leftovers <- s %% 3600

npjc

• use a cache environment in aaa_cache.R:

  • bg_ws for biogrid webservice.
  • use a function such as bg_ws_build() which assigns useful variables
    • url
    • uris (service endpoints)
    • access key
    • parameters

• in zzz.R:

npjc

# John Fox's numbers2words found here: 
# http://tolstoy.newcastle.edu.au/R/help/05/04/2715.html
numbers2words <- function(x){
  # helper
  helper <- function(x){
    
    digits <- rev(strsplit(as.character(x), "")[[1]])
    nDigits <- length(digits)
    if (nDigits == 1) as.vector(ones[digits])
    else if (nDigits == 2)

npjc

#' the name of the package we want to check
pkg <- "tidyr"
library(pkg, character.only = TRUE)
#' do the work
pacman::p_load(readr, dplyr, tidyr, ggplot2)
`%||%` <- function(a, b) if (!is.null(a)) a else b
ui <- getNamespaceExports(pkg)
only_funs <- unlist(lapply(ui, function(x) is.function(get(x))))
ui <- ui[only_funs]
l <- lapply(ui, function(f) {

npjc

pacman::p_load(readr, dplyr, tidyr, ggplot2)
library(partitions)
n <- 5
vals <- as.vector(parts(n))
len <- length(vals) / n
part <- rep(1:len, each = n)

d <- data_frame(vals, part)
d <- d %>% 
  group_by(part) %>%