Linux (debian/ubuntu)

In case you prefer to compile rawrr.exe from C# source code, please install the mono compiler and xbuild by installing the following Linux packages:

To install this package, start R (version “>=4.4”) and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("rawrr")

assemblies aka Common Intermediate Language bytecode - the download and install can be done on all platforms using the command:

rawDiag::checkRawrr

## function () 
## {
##     if (isFALSE(requireNamespace("BiocManager", quietly = TRUE))) 
##         stop("exec", "install.packages('BiocManager')")
##     if (isFALSE(requireNamespace("rawrr", quietly = TRUE))) 
##         stop("exec", "BiocManager::install('rawrr')")
##     if (isFALSE(file.exists(rawrr:::.rawrrAssembly()))) 
##         rawrr::installRawrrExe()
##     if (isFALSE(rawrr:::.isAssemblyWorking())) 
##         stop("rawrr assembly is not working. check if mono if available.")
##     TRUE
## }
## <bytecode: 0x562e89a33c68>
## <environment: namespace:rawDiag>

rawDiag::checkRawrr()

## Overwrite sourceUrl to https://fgcz-ms.uzh.ch/~cpanse/rawrr/dotnet//linux-x64/rawrr

## MD5 c51e3eb46ba5633b9763e94e9d09769c /github/home/.cache/R/rawrr/rawrrassembly/linux-x64/rawrr

## [1] TRUE

rawrr::installRawrrExe()

## NULL

rawrr::rawrrAssemblyPath()

## [1] "/github/home/.cache/R/rawrr/rawrrassembly/linux-x64"

rawrr::rawrrAssemblyPath() |> list.files()

## [1] "rawrr"

for more information please read the INSTALL file in the rawrr package.

Input

fetch example Orbitrap raw files from ExperimentHub’s tartare package.

library(ExperimentHub)

## Loading required package: BiocGenerics

## Loading required package: generics

## 
## Attaching package: 'generics'

## The following objects are masked from 'package:base':
## 
##     as.difftime, as.factor, as.ordered, intersect, is.element, setdiff,
##     setequal, union

## 
## Attaching package: 'BiocGenerics'

## The following objects are masked from 'package:stats':
## 
##     IQR, mad, sd, var, xtabs

## The following objects are masked from 'package:base':
## 
##     Filter, Find, Map, Position, Reduce, anyDuplicated, aperm, append,
##     as.data.frame, basename, cbind, colnames, dirname, do.call,
##     duplicated, eval, evalq, get, grep, grepl, is.unsorted, lapply,
##     mapply, match, mget, order, paste, pmax, pmax.int, pmin, pmin.int,
##     rank, rbind, rownames, sapply, saveRDS, table, tapply, unique,
##     unsplit, which.max, which.min

## Loading required package: AnnotationHub

## Loading required package: BiocFileCache

## Loading required package: dbplyr

ExperimentHub::ExperimentHub() -> eh
normalizePath(eh[["EH3222"]]) -> EH3222

## see ?tartare and browseVignettes('tartare') for documentation

## downloading 1 resources

## retrieving 1 resource

## loading from cache

normalizePath(eh[["EH4547"]]) -> EH4547

## see ?tartare and browseVignettes('tartare') for documentation

## downloading 1 resources

## retrieving 1 resource

## loading from cache

(rawfileEH3222 <- paste0(EH3222, ".raw"))

## [1] "/github/home/.cache/R/ExperimentHub/18b050f8b9ce_3238.raw"

if (!file.exists(rawfileEH3222)){
  file.copy(EH3222, rawfileEH3222)
}

## [1] TRUE

(rawfileEH4547 <- paste0(EH4547, ".raw"))

## [1] "/github/home/.cache/R/ExperimentHub/18b056e5021f_4590.raw"

if (!file.exists(rawfileEH4547)){
  file.copy(EH4547, rawfileEH4547)
}

## [1] TRUE

c(rawfileEH3222, rawfileEH4547) -> rawfile

Of note, the proprietary .Net assemblies (Shofstahl 2018) require a file extentention of .raw. Therfore we have to rename the EH files and add the .raw suffix.

list meta data of the raw files.

(rawfile |>
  lapply(FUN = rawrr::readFileHeader) -> rawFileHeader)

## [[1]]
## [[1]]$`RAW file`
## [1] "18b050f8b9ce_3238.raw"
## 
## [[1]]$`RAW file version`
## [1] "66"
## 
## [[1]]$`Creation date`
## [1] "7/16/2019 5:56:24 PM"
## 
## [[1]]$Operator
## [1] "lumos"
## 
## [[1]]$`Number of instruments`
## [1] 2
## 
## [[1]]$Description
## [1] ""
## 
## [[1]]$`Instrument model`
## [1] "Orbitrap Fusion Lumos"
## 
## [[1]]$`Instrument name`
## [1] "Orbitrap Fusion Lumos"
## 
## [[1]]$`Instrument method`
## [1] "C:/Xcalibur/methods/p3181/methMelt_GT20_RT35.meth"
## 
## [[1]]$`Serial number`
## [1] "FSN20583"
## 
## [[1]]$`Software version`
## [1] "3.1.2412.25"
## 
## [[1]]$`Firmware version`
## [1] ""
## 
## [[1]]$Units
## [1] "None"
## 
## [[1]]$`Mass resolution`
## [1] "0.500"
## 
## [[1]]$`Number of scans`
## [1] 8742
## 
## [[1]]$`Number of ms2 scans`
## [1] 2346
## 
## [[1]]$`Scan range`
## [1]    1 8742
## 
## [[1]]$`Time range`
## [1]  0.00 35.01
## 
## [[1]]$`Mass range`
## [1]   91 2000
## 
## [[1]]$`Scan filter (first scan)`
## [1] "FTMS + c ESI Full ms [350.0000-2000.0000]"
## 
## [[1]]$`Scan filter (last scan)`
## [1] "FTMS + c ESI Full ms [350.0000-2000.0000]"
## 
## [[1]]$`Total number of filters`
## [1] "2205"
## 
## [[1]]$`Sample name`
## [1] ""
## 
## [[1]]$`Sample id`
## [1] "1:A,5"
## 
## [[1]]$`Sample type`
## [1] "Unknown"
## 
## [[1]]$`Sample comment`
## [1] ""
## 
## [[1]]$`Sample vial`
## [1] "1:B,1"
## 
## [[1]]$`Sample volume`
## [1] "0"
## 
## [[1]]$`Sample injection volume`
## [1] "2"
## 
## [[1]]$`Sample row number`
## [1] "0"
## 
## [[1]]$`Sample dilution factor`
## [1] "1"
## 
## [[1]]$`Sample barcode`
## [1] ""
## 
## [[1]]$`User text 0`
## [1] ""
## 
## [[1]]$`User text 1`
## [1] ""
## 
## [[1]]$`User text 2`
## [1] ""
## 
## [[1]]$`User text 3`
## [1] ""
## 
## [[1]]$`User text 4`
## [1] ""
## 
## 
## [[2]]
## [[2]]$`RAW file`
## [1] "18b056e5021f_4590.raw"
## 
## [[2]]$`RAW file version`
## [1] "66"
## 
## [[2]]$`Creation date`
## [1] "11/16/2018 9:58:53 AM"
## 
## [[2]]$Operator
## [1] "QexactiveHF"
## 
## [[2]]$`Number of instruments`
## [1] 2
## 
## [[2]]$Description
## [1] ""
## 
## [[2]]$`Instrument model`
## [1] "Q Exactive HF Orbitrap"
## 
## [[2]]$`Instrument name`
## [1] "Q Exactive HF Orbitrap"
## 
## [[2]]$`Instrument method`
## [1] "C:/Xcalibur/methods/__QCloud/current_method/forward trap elute/autoQC01_TRAP_GT20min_RT35min.meth"
## 
## [[2]]$`Serial number`
## [1] "Exactive Series slot #2496"
## 
## [[2]]$`Software version`
## [1] "2.9-290204/2.9.2.2947"
## 
## [[2]]$`Firmware version`
## [1] "rev. 1"
## 
## [[2]]$Units
## [1] "None"
## 
## [[2]]$`Mass resolution`
## [1] "0.500"
## 
## [[2]]$`Number of scans`
## [1] 21881
## 
## [[2]]$`Number of ms2 scans`
## [1] 20885
## 
## [[2]]$`Scan range`
## [1]     1 21881
## 
## [[2]]$`Time range`
## [1]  0 35
## 
## [[2]]$`Mass range`
## [1]  100 1805
## 
## [[2]]$`Scan filter (first scan)`
## [1] "FTMS + c NSI Full ms [350.0000-1800.0000]"
## 
## [[2]]$`Scan filter (last scan)`
## [1] "FTMS + c NSI Full ms2 [email protected] [100.0000-1205.0000]"
## 
## [[2]]$`Total number of filters`
## [1] "22"
## 
## [[2]]$`Sample name`
## [1] "autoQC01"
## 
## [[2]]$`Sample id`
## [1] "NA"
## 
## [[2]]$`Sample type`
## [1] "Unknown"
## 
## [[2]]$`Sample comment`
## [1] ""
## 
## [[2]]$`Sample vial`
## [1] "1:F,8"
## 
## [[2]]$`Sample volume`
## [1] "0"
## 
## [[2]]$`Sample injection volume`
## [1] "2"
## 
## [[2]]$`Sample row number`
## [1] "0"
## 
## [[2]]$`Sample dilution factor`
## [1] "0"
## 
## [[2]]$`Sample barcode`
## [1] ""
## 
## [[2]]$`User text 0`
## [1] "1000"
## 
## [[2]]$`User text 1`
## [1] ""
## 
## [[2]]$`User text 2`
## [1] "FGCZ"
## 
## [[2]]$`User text 3`
## [1] ""
## 
## [[2]]$`User text 4`
## [1] ""

readRaw - read Orbitrap raw file

read the two instrument raw files by using the rawDiag package.

rawfile |>
  lapply(FUN = rawDiag::readRaw) |>
  Reduce(f = rbind) -> x

## reading index for 18b050f8b9ce_3238.raw...

## determining ElapsedScanTimesec ...

## reading trailer AGC ...

## reading trailer Orbitrap Resolution ...

## reading trailer Ion Injection Time (ms) ...

## reading TIC ...

## reading BasePeakIntensity ...

## reading took 5.622 seconds.

## reading index for 18b056e5021f_4590.raw...

## determining ElapsedScanTimesec ...

## reading trailer LM m/z-Correction (ppm) ...

## reading trailer AGC ...

## reading trailer AGC PS Mode ...

## reading trailer FT Resolution ...

## reading trailer Ion Injection Time (ms) ...

## reading TIC ...

## reading BasePeakIntensity ...

## reading took 11.821 seconds.

  #BiocParallel::bplapply(FUN = rawDiag::readRaw) |>

Output - Visualization

This package provides several plot functions tailored toward MS data. The following list shows all available plot methods.

library(rawDiag)
ls("package:rawDiag") |>
  grep(pattern = '^plot', value = TRUE) -> pm

pm |>
  knitr::kable(col.names = "package:rawDiag plot functions")

An inherent problem of visualizing data is the fact that depending on the data at hand, specific visualizations lose their usefulness, e.g., overplotting in a scatter plot if too many data points are present. To address this problem, we implemented most of the plot functions in different versions inspired by the work of Cleveland (1993), Sarkar (2008), and Wickham (2009). The data can be displayed in trellis plot manner using the faceting functionality of ggplot2. Alternatively, overplotting using color coding or violin plots based on descriptive statistics values can be chosen, which allows the user to interactively change the appearance of the plots based on the situation at hand. For instance, a large number of files are best visualized by violin plots, giving the user an idea about the distribution of the data points. On the basis of this, a smaller subset of files can be selected and visualized with another technique.

The code snippet below applies all plot methods on the example data.

pm |> 
  lapply(FUN = function(plotFUN) {
    lapply(c('trellis'), function(method) {
      message("plotting", plotFUN, "using method", method, "...")
      do.call(plotFUN, list(x, method)) 
    })
  }) 

## plottingplotChargeStateusing methodtrellis...

## plottingplotCycleLoadusing methodtrellis...

## plottingplotCycleTimeusing methodtrellis...

## plottingplotInjectionTimeusing methodtrellis...

## plottingplotLockMassCorrectionusing methodtrellis...

## plottingplotMassDistributionusing methodtrellis...

## plottingplotMzDistributionusing methodtrellis...

## plottingplotPrecursorHeatmapusing methodtrellis...

## plottingplotScanTimeusing methodtrellis...

## plottingplotTicBasepeakusing methodtrellis...

## [[1]]
## [[1]][[1]]

## 
## 
## [[2]]
## [[2]][[1]]

## `geom_smooth()` using formula = 'y ~ x'

## 
## 
## [[3]]
## [[3]][[1]]

## 
## 
## [[4]]
## [[4]][[1]]

## 
## 
## [[5]]
## [[5]][[1]]

## Warning: Removed 6164 rows containing non-finite outside the scale range
## (`stat_smooth()`).

## Warning: Removed 6164 rows containing missing values or values outside the scale range
## (`geom_line()`).

## 
## 
## [[6]]
## [[6]][[1]]

## 
## 
## [[7]]
## [[7]][[1]]

## 
## 
## [[8]]
## [[8]][[1]]

## 
## 
## [[9]]
## [[9]][[1]]

## 
## 
## [[10]]
## [[10]][[1]]

The appearance of each plot depends on the instrument, sample, and method used to acquire the data. Therefore, it is hard to say what each ideal plot should look like. In particular, in the example above, we use data generated on an Orbitrap Fusion Lumos, 18b050f8b9ce_3238.raw and Q Exactive HF Orbitrap, 18b056e5021f_4590.raw instrument using data-independent acquisition (DIA) (Bruderer et al. 2017) and data-dependent acquisition (DDA) methods. For more information on the plot methods and its application, please read the package man pages and the application examples in the manuscript (Trachsel et al. 2018).