junikimm717
/
Patternmatch
1
0
Fork 0
Code Issues Pull Requests Projects Releases 2 Wiki Activity
Browse Source

noninteractive corrections and reformat

master
Juni Kim 3 years ago
parent
f24f59c93c
commit
02b5115a28
2 changed files with 97 additions and 66 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 2
      .gitignore
  2. 161
      src/script.def.R

2
.gitignore
View File

@ -2,3 +2,5 @@
/data
/.RData
/.Rhistory
/.Rproj.user
/*.Rproj

161
src/script.def.R
View File

@ -4,18 +4,22 @@ library("stringr")
library("parallel")
# Configurations #############################################################
# file : decides which file to read in data from #############################
file <- "/path/to/csv"
# file to read from
input.filename <- ""
# separator to use (\t for tabs, "," for CSV)
input.sep <- ","
# All isotopes to check for
check_isos <- c("37Cl", "81Br", "34S")
check_isos <- c("37Cl", "81Br")
# Minimum size of a cluster
min_cluster_size <- 2
# Number of cores to be used (will be adjusted if it exceeds the true number of cores)
# Number of cores to be used in pattern.search evaluation
# (will be adjusted if it exceeds the true number of cores)
use_cores <- 6
# Table name configuration
# Column name for m/z
@ -28,56 +32,61 @@ columns.intensity <- "Intensity"
columns.spectra <- "Spectra_Number"
# output options
# Number of highest intensities to display in output
output.intensities <- 5
# Verbose output
verbose.enable <- FALSE
verbose.enable <- TRUE
# output directory must already exist.
verbose.outputdir <- "/path/to/directory"
verbose.outputdir <- ""
# Script #####################################################################
## Defining/setting variables ################################################
# C-13 is required in the rules of pattern.search, so it must be included. ###
# C-13 is required in the rules of pattern.search.
search_isos <- check_isos
iso_length <- length(search_isos)
if (!("13C" %in% search_isos)) {
search_isos <- append(search_isos, "13C")
}
# Read in the Table and sort by spectra ID
table <- read.table(file, header=TRUE, sep=",")
table <- table[order(table[,columns.spectra]),]
table <- read.table(input.filename, header = TRUE, sep = input.sep)
table <- table[order(table[, columns.spectra]), ]
# Organize the tables by number
fragments <- max(table[,columns.spectra])
fragments <- max(table[, columns.spectra])
# set use_cores to safe amount
use_cores = min(use_cores, detectCores()-1)
use_cores = min(use_cores, detectCores() - 1)
# lower bound of indices per fragment
# lower bound of indices per fragment
# (sorting guarantees that data points of same fragment are together)
minint <- rep(0,fragments)
minint <- rep(0, fragments)
# upper bound of indices per fragment
maxint <- rep(0,fragments)
# memoizes as to
usable <- rep(FALSE,fragments)
maxint <- rep(0, fragments)
# memoizes as to
usable <- rep(FALSE, fragments)
# initialize isotopes.
data(isotopes)
isos <- make.isos(isotopes,use_isotopes=search_isos,
use_charges=rep(1, length(search_isos)))
isos <- make.isos(isotopes,
use_isotopes = search_isos,
use_charges = rep(1, length(search_isos)))
## Setting functions #########################################################
getdata <- function(fragment, key) {
if (! usable[fragment]) {
stop(str_interp("Fragment $[d]{fragment} does not exist in the data set",
list(fragment=fragment)))
if (!usable[fragment]) {
stop(str_interp(
"Fragment $[d]{fragment} does not exist in the data set",
list(fragment = fragment)
))
}
return(table[minint[fragment]:maxint[fragment],key])
return(table[minint[fragment]:maxint[fragment], key])
}
# Add all data frames as necessary for evaluation.
@ -87,7 +96,11 @@ getdataframe <- function (fragment) {
mz <- getdata(fragment, columns.mz)
time <- getdata(fragment, columns.time)
Intensity <- getdata(fragment, columns.intensity)
return(data.frame(mz=mz, Intensity=Intensity,time=time))
return(data.frame(
mz = mz,
Intensity = Intensity,
time = time
))
}
# returns both pattern.search result and fragment number.
@ -97,17 +110,18 @@ diagnostics <- function(fragment) {
ptrn <- pattern.search(
points,
isos,
cutint=1000,
rttol=c(-20,20),
cutint = 1000,
rttol = c(-20, 20),
# kept because of gc limitations.
mztol=3,
mzfrac=0.1,
ppm=TRUE,
inttol=0.05,
rules=rep(TRUE,11),
deter=FALSE,
entry=50
);
mztol = 3,
mzfrac = 0.1,
ppm = TRUE,
inttol = 0.05,
rules = rep(TRUE, 11),
deter = FALSE,
entry = 50
)
return(c(ptrn, fragment))
}
@ -115,7 +129,7 @@ diagnostics <- function(fragment) {
positive <- function(result) {
res <- result$`Counts of isotopes`
v <- res[res$"isotope" %in% check_isos,"peak counts"]
v <- res[res$"isotope" %in% check_isos, "peak counts"]
return (!all(v %in% c(0)))
}
@ -125,35 +139,38 @@ derive.fragment <- function(result) {
derive.iso <- function(result) {
res <- result$`Counts of isotopes`
return (res[res$"isotope" %in% check_isos,c("isotope", "group counts")])
return (res[res$"isotope" %in% check_isos, c("isotope", "group counts")])
}
derive.intensity <- function(result) {
ptrn <- result$Patterns
N <- max(output.intensities, nrow(result))
inds <- order(ptrn[,columns.intensity], decreasing=TRUE)[1:N]
inds <- order(ptrn[, columns.intensity], decreasing = TRUE)[1:N]
return(ptrn[inds, c(2, 1, 3)])
}
derive.average <- function(result) {
ptrn <- result$Patterns[,2]
ptrn <- result$Patterns[, 2]
return(mean(ptrn))
}
derive.frame <- function(result) {
res <- list(
derive.fragment(result),
derive.iso(result),
derive.intensity(result),
derive.average(result)
)
names(res) <- c("Fragment_ID", "Peaks", "Intensities", "Average_time")
derive.fragment(result),
derive.iso(result),
derive.intensity(result),
derive.average(result)
)
names(res) <-
c("Fragment_ID", "Peaks", "Intensities", "Average_time")
return(res)
}
verbose.dump <- function(result) {
path <- file.path(verbose.outputdir, paste(derive.fragment(result), ".txt",
sep=""))
path <-
file.path(verbose.outputdir,
paste(derive.fragment(result), ".txt",
sep = ""))
sink(path)
dput(result)
sink()
@ -165,7 +182,7 @@ verbose.dump <- function(result) {
for (i in seq(1, nrow(table))) {
fragment <- table[i, columns.spectra]
if (! usable[fragment]) {
if (!usable[fragment]) {
minint[fragment] <- i
}
maxint[fragment] <- max(maxint[fragment], i)
@ -175,39 +192,51 @@ for (i in seq(1, nrow(table))) {
# make fragment unusable if it does not contain enough data points.
for (i in 1:fragments) {
if (maxint[i] - minint[i] + 1 < min_cluster_size)
usable[i] = FALSE
usable[i] <- FALSE
}
# Filter all usable fragments
use <- Filter(function(x) usable[x], 1:fragments)
use <- Filter(function(x)
usable[x], 1:fragments)
# Apply diagnostics function to all usable fragments (in parallel).
results <- mclapply(use, diagnostics, mc.cores=use_cores)
results <- mclapply(use, diagnostics, mc.cores = use_cores)
results.positive <- Filter(function(x) positive(x), results)
results.positive <- Filter(function(x)
positive(x), results)
# print to files if verbose output requested
if (verbose.enable) {
if (!dir.exists(verbose.outputdir)) {
stop(str_interp("Directory $[s]{dir} does not exist",
list(dir=verbose.outputdir)))
stop(str_interp(
"Directory $[s]{dir} does not exist",
list(dir = verbose.outputdir)
))
}
res <- readline(prompt=paste("Are you sure you want to overwrite files in ",
verbose.outputdir, "? [y/N] "))
if (res != "y") {
stop("Process aborted.")
if (interactive()) {
res <-
readline(
prompt = paste(
"Are you sure you want to overwrite files in ",
verbose.outputdir,
"? [y/N] "
)
)
if (res != "y")
{
stop("Process aborted.")
}
}
print(paste("printing output to ", verbose.outputdir))
mapply(verbose.dump, results.positive)
lapply(results.positive, verbose.dump)
}
result.frame <- mapply(derive.frame, results.positive)
result.fragment <- mapply(derive.fragment, results.positive)
result.iso <- mapply(derive.iso, results.positive)
result.intensity <- mapply(derive.intensity, results.positive)
result.average <- mapply(derive.average, results.positive)
print(result.fragment)
result.frame <- lapply(results.positive, derive.frame)
result.fragment <- lapply(results.positive, derive.fragment)
result.iso <- lapply(results.positive, derive.iso)
result.intensity <- lapply(results.positive, derive.intensity)
result.average <- lapply(results.positive, derive.average)
##############################################################################
print("All Fragments that contain desired isotopes:")
print(result.frame)
Write Preview
Loading…
Cancel
Save