chasemc

# Need some subset of these packages:
#library(readxl)
#library(sf)
#library(sp)
#library(leaflet)
#library(leaflet.extras)
#library(dplyr)
#library(shiny)
#library(ggplot2)
#library(maps)

chasemc

What is continuous deployment (CD)?

Why CD?

• Reproducible and easy deliverables
  • Missing link... how do we know an output came from the latest version of code?
  • A majority of R users can't associate a knitted report to the code version
• Delivering R-based software (Shiny, Plumber, etc)

CD for Shiny

chasemc

gene <- "16S ribosomal RNA[product]"

a <- "ATCC 10762=ATCC 23884=CBS 434.51=DSM 40127=IFO 12594=IFO 12843=IMET 43577=ISP 5127=JCM 4008=JCM 4624=Lederle A-377=LL A-377=NCIB 8234=NRRL 2209=RIA 1129=Waksman 3550A=WC 3550"
a <- strsplit(a, "=")[[1]]
b <- glue::glue("{a}[All Fields]", sep=" ")
b <- paste0(b, collapse = " OR ")
d <- glue::glue(b, " AND {gene}")

e <- rentrez::entrez_search(db="nuccore", term=d, retmax=10)

chasemc

converter <- function(inputDirectory,
                      ouputDirectory) {
  
  a <- list.files(inputDirectory,
                  full.names = T)
  
  b <- MALDIquantForeign::import(a,
                                 centroided = FALSE)
  
  

chasemc

# This is not mine. I took it from: https://stackoverflow.com/a/38743324/7776088

#' Add curent version string to package dependencies
#'
#' Will \code{cat} out a cut/paste-able set of fields for a
#' \code{DESCRIPTION} file with minimum required versions for
#' each package based upon currently available package vesions
#' in CRAN.
#'
#' @param pkg package description, can be path or package name

chasemc

profile.mzML
  scan 100-110
  convert to mzML
  
centroid.mzML
  scan 100-110
  peak picking = vendor
  convert to mzML
  
cwt.mzML

chasemc

---
title: '2019-09-03'
author: "Chase Clark"
date: "9/3/2019"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

chasemc

a <- 'C:/Users/chase/Downloads/2019_10_30_christie/bruker'


file_names <- list.files(a)
file_names_path <- list.files(a, full.names = TRUE)

z <- sapply(file_names, function(x) strsplit(x, "0_")[[1]][[2]]  )

chasemc

library(ggplot2)
library(mzR)

mass <- c( 654.3920, 668.3920)

numCores <- parallel::detectCores()
numCores <- ifelse(numCores > 2,
                   numCores - 1,
                   1)

chasemc

# Requires IDBac function findMSconvert()
parallel_msconvert <- function(directory){

  # File paths
  raw_path <- file.path(directory)
  raw_files <- list.files(raw_path,
                          full.names = TRUE)
  mzml_dir <- file.path(dirname(raw_path),
                        "mzml")
  dir.create(mzml_dir)