Merge branch 'devel' into import_methods

.github/workflows/check-bioc.yml

@@ -54,8 +54,8 @@ jobs:
       matrix:
         config:
           - { os: ubuntu-latest, r: 'devel', bioc: 'devel', cont: "bioconductor/bioconductor_docker:devel", rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest" }
-          - { os: macOS-latest, r: 'devel', bioc: '3.19'}
-          - { os: windows-latest, r: 'devel', bioc: '3.19'}
+          - { os: macOS-latest, r: 'next', bioc: '3.19'}
+          - { os: windows-latest, r: 'next', bioc: '3.19'}
     env:
       R_REMOTES_NO_ERRORS_FROM_WARNINGS: true
       RSPM: ${{ matrix.config.rspm }}
@@ -160,12 +160,12 @@ jobs:
       - name: Install BiocManager
         run: |
           message(paste('****', Sys.time(), 'installing BiocManager ****'))
-          remotes::install_cran("BiocManager")
+          remotes::install_cran("BiocManager", type = "source")
         shell: Rscript {0}
 
       - name: Set BiocVersion
         run: |
-          BiocManager::install(version = "${{ matrix.config.bioc }}", ask = FALSE)
+          BiocManager::install(version = "${{ matrix.config.bioc }}", ask = FALSE, type = "source")
         shell: Rscript {0}
 
       - name: Install dependencies pass 1
@@ -177,45 +177,48 @@ jobs:
           ## https://github.com/r-lib/remotes/issues/296
           ## Ideally, all dependencies should get installed in the first pass.
 
+          ## Workaround for problems with cached S4objects in binary packages
+          BiocManager::install("GenomeInfoDb", force = TRUE, type = "source")
+          BiocManager::install("BiocParallel", force = TRUE, type = "source")
+          BiocManager::install("S4Vectors", force = TRUE, type = "source")
+          BiocManager::install("SummarizedExperiment", force = TRUE, type = "source")
+          ## install xcms with dependencies - to ensure dependencies are installed from source;
+          ## somehow install_local installs binary packages instead.
+          BiocManager::install("mzR", force = TRUE)
+          BiocManager::install("MSnbase", force = TRUE, type = "source")
+          BiocManager::install("xcms", force = TRUE, type = "source", dependencies = TRUE)
+          BiocManager::install("faahKO", type = "source")
+
           ## Pass #1 at installing dependencies
-          BiocManager::install(c("ncdf4", "mzR"))
           message(paste('****', Sys.time(), 'pass number 1 at installing dependencies: local dependencies ****'))
-          remotes::install_local(dependencies = TRUE, repos =
-          BiocManager::repositories(), build_vignettes = FALSE, upgrade = TRUE)
+          remotes::install_local(dependencies = TRUE, repos = BiocManager::repositories(), build_vignettes = FALSE, build_manual = FALSE, type = "source")
 
-          BiocManager::install(c("rmarkdown", "BiocStyle"))
+          BiocManager::install(c("rmarkdown", "BiocStyle"), type = "source")
         continue-on-error: true
         shell: Rscript {0}
 
       - name: Install dependencies pass 2
         run: |
           ## Pass #2 at installing dependencies
           message(paste('****', Sys.time(), 'pass number 2 at installing dependencies: any remaining dependencies ****'))
-          remotes::install_local(dependencies = TRUE, repos = BiocManager::repositories(), build_vignettes = FALSE, upgrade = TRUE)
+          remotes::install_local(dependencies = TRUE, repos = BiocManager::repositories(), build_vignettes = FALSE, type = "source")
 
           ## Manually install packages that seem to be skipped.
           message(paste('****', Sys.time(), 'force installation of selected packages  ****'))
-          BiocManager::install(c("faahKO"))
-          BiocManager::install("ProtGenerics")
-          BiocManager::install("MSnbase")
-          BiocManager::install("mzR", type = "source", force = TRUE)
-          BiocManager::install("Spectra")
-          BiocManager::install("MsBackendMgf")
-          BiocManager::install("MetaboCoreUtils")
-          BiocManager::install("magick")
-          BiocManager::install("RforMassSpectrometry/MsExperiment")
+          BiocManager::install("RforMassSpectrometry/MsCoreUtils", force = TRUE)
+          BiocManager::install("magick", type = "source")
 
           ## For running the checks
           message(paste('****', Sys.time(), 'installing rcmdcheck and BiocCheck ****'))
-          remotes::install_cran("rcmdcheck")
-          BiocManager::install(c("BiocCheck", "DBI"))
+          remotes::install_cran("rcmdcheck", type = "source")
+          BiocManager::install("BiocCheck", type = "source")
         shell: Rscript {0}
 
       - name: Install BiocGenerics
         if:  env.has_RUnit == 'true'
         run: |
           ## Install BiocGenerics
-          BiocManager::install("BiocGenerics")
+          BiocManager::install("BiocGenerics", type = "source")
         shell: Rscript {0}
 
       - name: Install covr

DESCRIPTION

@@ -1,5 +1,5 @@
 Package: xcms
-Version: 4.1.12
+Version: 4.1.14
 Title: LC-MS and GC-MS Data Analysis
 Description: Framework for processing and visualization of chromatographically
     separated and single-spectra mass spectral data. Imports from AIA/ANDI NetCDF,
@@ -41,8 +41,8 @@ Authors@R: c(
 	   role = "ctb",
 	   comment = c(ORCID = "0000-0002-5492-6904")),
 	   person(given = "Carl", family = "Brunius",
-	   email = "carl.brunius@chalmers.se", 
-	   role = "ctb", 
+	   email = "carl.brunius@chalmers.se",
+	   role = "ctb",
 	   comment = c(ORCID = "0000-0003-3957-870X"))
 	   )
 Depends:
@@ -104,11 +104,11 @@ Collate:
     'MPI.R'
     'MsExperiment-functions.R'
     'MsExperiment.R'
+    'XcmsExperiment.R'
     'PlainTextParam.R'
     'RDataParam.R'
     'XcmsExperiment-functions.R'
     'XcmsExperiment-plotting.R'
-    'XcmsExperiment.R'
     'c.R'
     'cwTools.R'
     'databases.R'

NEWS.md

@@ -1,5 +1,17 @@
 # xcms 4.1
 
+## Changes in version 4.1.13
+
+- Fix for issue #734. XIC plot is is now working with MS2 Data.
+
+
+## Changes in version 4.1.13
+
+- Add parameter `rtimeDifferenceThreshold` to `ObiwarpParam` allowing to
+  customize the threshold used by obiwarp to determine whether *gaps* are
+  present in the sequence of retention times of a sample. This addresses/fixes
+  issue #739.
+
 ## Changes in version 4.1.12
 
 - Implementation of the `LamaParama` class and method for the `adjustRtime()`

R/AllGenerics.R

@@ -194,6 +194,18 @@ setGeneric("addProcessHistory", function(object, ...)
 #'     start and end points and `response = 100` warping using all bijective
 #'     anchors.
 #'
+#' @param rtimeDifferenceThreshold For `ObiwarpParam`: `numeric(1)` defining
+#'     the threshold to identify a *gap* in the sequence of retention times of
+#'     (MS1) spectra of a sample/file. A gap is defined if the difference in
+#'     retention times between consecutive spectra is
+#'     `> rtimeDifferenceThreshold` of the median observed difference or
+#'     retenion times of that data sample/file. Spectra with an retention time
+#'     after such a *gap* will not be adjusted. The default for this parameter
+#'     is `rtimeDifferenceThreshold = 5`. For Waters data with lockmass scans
+#'     or LC-MS/MS data this might however be a too low threshold and it should
+#'     be increased. See also
+#'     [issue #739](https://github.com/sneumann/xcms/issues/739).
+#'
 #' @param smooth For `PeakGroupsParam`: `character(1)` defining the function to
 #'     be used to interpolate corrected retention times for all peak groups.
 #'     Can be either `"loess"` or `"linear"`.

R/DataClasses.R

@@ -1522,7 +1522,8 @@ setClass("ObiwarpParam",
                    localAlignment = "logical",
                    initPenalty = "numeric",
                    subset = "integer",
-                   subsetAdjust = "character"),
+                   subsetAdjust = "character",
+                   rtimeDifferenceThreshold = "numeric"),
          contains = "Param",
          prototype = prototype(
              binSize = 1,
@@ -1536,7 +1537,8 @@ setClass("ObiwarpParam",
              localAlignment = FALSE,
              initPenalty = 0,
              subset = integer(),
-             subsetAdjust = "average"),
+             subsetAdjust = "average",
+             rtimeDifferenceThreshold = 5),
          validity = function(object) {
              msg <- character()
              if (length(object@binSize) > 1 |

R/MsExperiment-functions.R

@@ -333,6 +333,7 @@
 
 .mse_obiwarp_chunks <- function(x, param, msLevel = 1L, chunkSize = 1L,
                                 BPPARAM = bpparam()) {
+    message("value ", param@rtimeDifferenceThreshold)
     rt_raw <- split(rtime(x), fromFile(x))
     subset_idx <- subset(param)
     if (length(subset_idx))

R/PlainTextParam.R

@@ -1,5 +1,6 @@
-#' @title Store/load contents of `MsExperiment` and `XcmsExperiment` objects
-#' as/from plain text files
+#' @include XcmsExperiment.R
+#' @title Store contents of `MsExperiment` and `XcmsExperiment` objects as
+#' plain text files
 #'
 #' @name PlainTextParam
 #'

R/XcmsExperiment-plotting.R

@@ -380,12 +380,13 @@ setMethod(
     fns <- basename(fileNames(x))
     for (i in seq_along(x)) {
         z <- x[i]
-        lst <- as(filterMsLevel(spectra(z), msLevel = msLevel), "list")
+        flt <- filterMsLevel(spectra(z), msLevel = msLevel)
+        lst <- as(flt, "list")
         lns <- lengths(lst) / 2
         lst <- do.call(rbind, lst)
         if (!length(lst))
             next
-        df <- data.frame(rt = rep(rtime(z), lns), lst)
+        df <- data.frame(rt = rep(rtime(flt), lns), lst)
         colnames(df)[colnames(df) == "intensity"] <- "i"
         do.call(MSnbase:::.plotXIC,
                 c(list(x = df, main = fns[i], layout = NULL), dots))

R/functions-OnDiskMSnExp.R

@@ -448,15 +448,15 @@ findPeaks_MSW_Spectrum_list <- function(x, method = "MSW", param) {
     ## median difference between spectras' scan time.
     mstdiff <- median(c(scantime1_diff, scantime2_diff), na.rm = TRUE)
 
-    mst1 <- which(scantime1_diff > 5 * mstdiff)[1]
+    mst1 <- which(scantime1_diff > param@rtimeDifferenceThreshold * mstdiff)[1]
     if (!is.na(mst1)) {
-        message("Found gaps in scan times of the center sample: cut ",
+        warning("Found gaps in scan times of the center sample: cut ",
                 "scantime-vector at ", scantime1[mst1]," seconds.")
         scantime1 <- scantime1[seq_len(max(2, (mst1 - 1)))]
     }
-    mst2 <- which(scantime2_diff > 5 * mstdiff)[1]
+    mst2 <- which(scantime2_diff > param@rtimeDifferenceThreshold * mstdiff)[1]
     if (!is.na(mst2)) {
-        message("Found gaps in scan time. Cutting scantime-vector at ",
+        warning("Found gaps in scan time. Cutting scantime-vector at ",
                 scantime2[mst2]," seconds.")
         scantime2 <- scantime2[seq_len(max(2, (mst2 - 1)))]
     }

R/functions-Params.R

@@ -311,15 +311,17 @@ ObiwarpParam <- function(binSize = 1, centerSample = integer(), response = 1L,
                          gapExtend = numeric(), factorDiag = 2, factorGap = 1,
                          localAlignment = FALSE, initPenalty = 0,
                          subset = integer(),
-                         subsetAdjust = c("average", "previous")) {
+                         subsetAdjust = c("average", "previous"),
+                         rtimeDifferenceThreshold = 5) {
     subsetAdjust <- match.arg(subsetAdjust)
     new("ObiwarpParam", binSize = binSize,
         centerSample = as.integer(centerSample),
         response = as.integer(response), distFun = distFun,
         gapInit = gapInit, gapExtend = gapExtend, factorDiag = factorDiag,
         factorGap = factorGap, localAlignment = localAlignment,
         initPenalty = initPenalty, subset = as.integer(subset),
-        subsetAdjust = subsetAdjust)
+        subsetAdjust = subsetAdjust,
+        rtimeDifferenceThreshold = rtimeDifferenceThreshold[1L])
 }
 
 #' @return The \code{FillChromPeaksParam} function returns a

R/methods-Params.R

@@ -1265,7 +1265,8 @@ setMethod("plot", signature(x = "LamaParama"),
                               zero_weight = x@zeroWeight,
                               bs = x@bs)
     datap <- x@rtMap[[index]]
-    plot(datap, type = "p", xlab = xlab, ylab = ylab, col = colPoints, ...)
+    plot(datap[, 2L], datap[, 1L], type = "p", xlab = xlab, ylab = ylab,
+         col = colPoints, ...)
     points(model, type = "l", col = colFit)
 })