v0.7.9

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: MFassign
 Title: Molecular Formula Assignment for High Resolution metabolomics
-Version: 0.7.8
+Version: 0.7.9
 Authors@R: person("Jasen", "Finch", email = "jsf9@aber.ac.uk", role = c("aut", "cre"))
 Description: Molecular formula assignment for high resolution metabolomics.
 Depends: R (>= 3.5.0),
@@ -24,46 +24,49 @@ Imports: CHNOSZ,
     mzAnnotation,
     metabolyseR,
     ggrepel,
-    graphlayouts
+    graphlayouts,
+    future,
+    furrr
 Remotes: jasenfinch/mzAnnotation,
     jasenfinch/metabolyseR
 License: GPL (>= 3)
 Encoding: UTF-8
 LazyData: true
 RoxygenNote: 7.1.1
 Collate:
-        'allGenerics.R'
-        'allClasses.R'
-        'prepCorrelations-method.R'
-        'addIsoAssign-method.R'
-        'transformationAssign-method.R'
-        'relationships-method.R'
-        'assignmentParameters.R'
-        'assignMFs.R'
-        'MFgen.R'
-        'MFscore.R'
-        'addIsoScore.R'
-        'addMFs.R'
-        'calcComponents.R'
-        'assignMethods.R'
-        'peakData.R'
-        'LCassignment.R'
-        'MFassign.R'
-        'FIEassignment.R'
-        'doAssignment-method.R'
-        'continueAssignment.R'
-        'show-method.R'
-        'access-methods.R'
-        'summariseAssignment-method.R'
-        'plotNetwork-method.R'
-        'networkComponents.R'
-        'addNames.R'
-        'eliminate.R'
-        'recalcComponents.R'
-        'plotAdductDist-method.R'
-        'plotFeatureSolutions.R'
-        'calcCorrelations-method.R'
-        'filterCorrelations-method.R'
-        'plotSpectrum-method.R'
+        allGenerics.R
+        allClasses.R
+        prepCorrelations-method.R
+        addIsoAssign-method.R
+        transformationAssign-method.R
+        relationships-method.R
+        assignmentParameters.R
+        assignMFs.R
+        MFgen.R
+        MFscore.R
+        addIsoScore.R
+        addMFs.R
+        calcComponents.R
+        assignMethods.R
+        peakData.R
+        LCassignment.R
+        MFassign.R
+        FIEassignment.R
+        doAssignment-method.R
+        continueAssignment.R
+        show-method.R
+        access-methods.R
+        summariseAssignment-method.R
+        plotNetwork-method.R
+        networkComponents.R
+        addNames.R
+        eliminate.R
+        recalcComponents.R
+        plotAdductDist-method.R
+        plotFeatureSolutions.R
+        calcCorrelations-method.R
+        filterCorrelations-method.R
+        plotSpectrum-method.R
+        reexports.R
 Suggests: testthat,
     covr

NAMESPACE

@@ -5,6 +5,7 @@ export(assignmentParameters)
 export(continueAssignment)
 export(edges)
 export(nodes)
+export(plan)
 exportClasses(Assignment)
 exportClasses(AssignmentParameters)
 exportMethods(assignedData)
@@ -33,15 +34,19 @@ importFrom(dplyr,group_by)
 importFrom(dplyr,inner_join)
 importFrom(dplyr,left_join)
 importFrom(dplyr,mutate)
+importFrom(dplyr,mutate_at)
 importFrom(dplyr,n)
 importFrom(dplyr,rename)
 importFrom(dplyr,rowwise)
 importFrom(dplyr,select)
 importFrom(dplyr,semi_join)
 importFrom(dplyr,slice_sample)
 importFrom(dplyr,summarise)
-importFrom(dplyr,tbl_df)
 importFrom(dplyr,ungroup)
+importFrom(dplyr,vars)
+importFrom(furrr,furrr_options)
+importFrom(furrr,future_map)
+importFrom(future,plan)
 importFrom(ggplot2,aes)
 importFrom(ggplot2,coord_fixed)
 importFrom(ggplot2,element_blank)
@@ -100,10 +105,6 @@ importFrom(mzAnnotation,relationshipCalculator)
 importFrom(mzAnnotation,transformMF)
 importFrom(mzAnnotation,transformations)
 importFrom(parallel,detectCores)
-importFrom(parallel,makeCluster)
-importFrom(parallel,parApply)
-importFrom(parallel,parLapply)
-importFrom(parallel,stopCluster)
 importFrom(patchwork,plot_annotation)
 importFrom(patchwork,wrap_plots)
 importFrom(purrr,map)

R/addIsoAssign-method.R

@@ -2,7 +2,7 @@
 #' @importFrom stringr str_detect
 #' @importFrom mzAnnotation calcM calcMZ ppmError
 #' @importFrom igraph vertex.attributes V
-#' @importFrom parallel parLapply
+#' @importFrom furrr furrr_options
 
 setMethod('addIsoAssign',signature = 'Assignment',
           function(assignment){
@@ -30,21 +30,12 @@ setMethod('addIsoAssign',signature = 'Assignment',
 
             nM <- nrow(M)
 
-            slaves <- nrow(M) / 100 * mean(M$M)/100
-            slaves <-  ceiling(slaves)
-
-            if (slaves > parameters@nCores) {
-              slaves <- parameters@nCores
-            }
-
-            clus <- makeCluster(slaves,type = parameters@clusterType)
-
             MF <- M %>%
               ungroup() %>%
               slice_sample(n = nM) %>%
               split(1:nrow(.)) %>%
-              parLapply(cl = clus,function(x,parameters,M){
-                mf <- MFgen(x$M,x$mz,ppm = parameters@ppm) 
+              future_map(~{
+                mf <- MFgen(.x$M,.x$mz,ppm = parameters@ppm) 
 
                 if (nrow(mf) > 0) {
                   mf %>%
@@ -57,18 +48,19 @@ setMethod('addIsoAssign',signature = 'Assignment',
                     rowwise() %>%
                     mutate(Score = MFscore(MF),
                            `PPM Error` = abs(`PPM Error`),
-                           AddIsoScore = addIsoScore(Adduct,Isotope,parameters@adducts,parameters@isotopes)) %>%
-                    tbl_df() %>%
-                    filter(Score == min(Score,na.rm = T)) %>%
+                           AddIsoScore = addIsoScore(Adduct,
+                                                     Isotope,
+                                                     parameters@adducts,
+                                                     parameters@isotopes)) %>%
+                    ungroup() %>%
+                    filter(Score == min(Score,na.rm = TRUE)) %>%
                     filter(Score < parameters@maxMFscore)
                 } else {
                   return(NULL)
                 }
-              },parameters = parameters,M = M) %>% 
+              },.options = furrr_options(seed = 1234)) %>% 
               bind_rows()
 
-              stopCluster(clus)
-
             rel <- rel %>% 
               addMFs(MF) %>%
               filter(MF1 == MF2) %>%

R/allClasses.R

@@ -15,8 +15,7 @@
 #' @slot adductRules tibble containing adduct formation rules as returned by mzAnnotation::adducts()
 #' @slot isotopeRules tibble containing isotope rules as returned by mzAnnotation::isotopes()
 #' @slot transformationRules tibble containing transformation rules as returned by mzAnnotation::transformations()
-#' @slot nCores number of cores to use for parallisation
-#' @slot clusterType cluster type to use for parallisation
+#' @importFrom mzAnnotation transformations
 #' @export
 
 setClass('AssignmentParameters',
@@ -34,9 +33,26 @@ setClass('AssignmentParameters',
            transformations = 'character',
            adductRules = 'tbl_df',
            isotopeRules = 'tbl_df',
-           transformationRules = 'tbl_df',
-           nCores = 'numeric',
-           clusterType = 'character'
+           transformationRules = 'tbl_df'
+         ),
+         prototype = list(
+           technique = 'FIE',
+           correlations = list(method = 'pearson',pAdjustMethod = 'bonferroni',corPvalue = 0.05),
+           filter = list(rthresh = 0.7,n = 100000,rIncrement = 0.01,nIncrement = 20000),
+           maxM = 1000,
+           maxMFscore = 5,
+           ppm = 5,
+           limit = 0.001,
+           RTwindow = numeric(),
+           isotopes = c('13C','18O','13C2'),
+           adducts = list(n = c("[M-H]1-", "[M+Cl]1-", "[M+K-2H]1-", 
+                                "[M-2H]2-", "[M+Cl37]1-","[2M-H]1-"),
+                          p = c('[M+H]1+','[M+K]1+','[M+Na]1+','[M+K41]1+',
+                                '[M+NH4]1+','[M+2H]2+','[2M+H]1+')),
+           transformations = transformations()$`MF Change`,
+           adductRules = adducts(),
+           isotopeRules = isotopes(),
+           transformationRules = transformations()
          ))
 
 #' Assignment
@@ -65,4 +81,16 @@ setClass('Assignment',
            addIsoAssign = 'list',
            transAssign = 'list',
            assignments  = 'tbl_df'
+         ),
+         prototype = list(
+           log = list(date = date(),verbose = TRUE),
+           flags = character(),
+           parameters = new('AssignmentParameters'),
+           data = tibble(),
+           correlations = tibble(),
+           preparedCorrelations = tibble(),
+           relationships = tibble(),
+           addIsoAssign = list(),
+           transAssign = list(),
+           assignments  = tibble()
          ))

R/assignMFs.R

@@ -9,8 +9,8 @@
 #' @importFrom lubridate seconds_to_period
 #' @importFrom utils capture.output
 #' @examples 
+#' plan(future::sequential)
 #' p <- assignmentParameters('FIE')
-#' p@nCores <- 2
 #'
 #' assignment <- assignMFs(peakData,p)
 #'
@@ -37,17 +37,9 @@ assignMFs <- function(dat,parameters,verbose = TRUE) {
   }
 
   assignment <- new('Assignment',
-                    log = list(date = date(),verbose = verbose),
-                    flags = character(),
-                    parameters = parameters,
                     data = dat,
-                    correlations = tibble(),
-                    preparedCorrelations = tibble(),
-                    relationships = tibble(),
-                    addIsoAssign = list(),
-                    transAssign = list(),
-                    assignments  = tibble()
-  )
+                    parameters = parameters)
+  assignment@log$verbose <- verbose
 
  assignment <- assignment %>%
    doAssignment()

R/assignmentParameters.R

@@ -3,7 +3,6 @@
 #' @param technique technique to use for assignment. \code{NULL} prints available techniques
 #' @importFrom parallel detectCores
 #' @importFrom methods new
-#' @importFrom mzAnnotation transformations
 #' @export
 
 assignmentParameters <- function(technique = NULL){
@@ -12,77 +11,22 @@ assignmentParameters <- function(technique = NULL){
     cat('\nAvailable Techniques:',str_c('\n\t\t\t',str_c(availTechniques,collapse = '\n\t\t\t'),'\n'))
     p <- NULL
   } else {
+
     if (technique == 'FIE') {
-      p <- new('AssignmentParameters',
-          technique = 'FIE',
-          correlations = list(method = 'pearson',pAdjustMethod = 'bonferroni',corPvalue = 0.05),
-          filter = list(rthresh = 0.7,n = 100000,rIncrement = 0.01,nIncrement = 20000),
-          maxM = 600,
-          maxMFscore = 5,
-          ppm = 5,
-          limit = 0.001,
-          RTwindow = numeric(),
-          isotopes = c('13C','18O','13C2'),
-          adducts = list(n = c("[M-H]1-", "[M+Cl]1-", "[M+K-2H]1-", 
-                               "[M-2H]2-", "[M+Cl37]1-","[2M-H]1-"),
-                         p = c('[M+H]1+','[M+K]1+','[M+Na]1+','[M+K41]1+',
-                               '[M+NH4]1+','[M+2H]2+','[2M+H]1+')),
-          transformations = transformations()$`MF Change`,
-          adductRules = adducts(),
-          isotopeRules = isotopes(),
-          transformationRules = transformations(),
-          nCores = detectCores(),
-          clusterType = 'FORK'
-      )
+      p <- new('AssignmentParameters')
     }
     if (technique == 'RP-LC') {
       p <- new('AssignmentParameters',
           technique = 'RP-LC',
-          correlations = list(method = 'pearson',pAdjustMethod = 'bonferroni',corPvalue = 0.05),
-          filter = list(rthresh = 0.7,n = 100000,rIncrement = 0.01,nIncrement = 20000),
-          maxM = 600,
-          maxMFscore = 5,
-          ppm = 5,
-          limit = 0.001,
-          RTwindow = 1/60,
-          isotopes = c('13C','18O','13C2'),
-          adducts = list(n = c("[M-H]1-", "[M+Cl]1-", "[M+K-2H]1-", 
-                               "[M-2H]2-", "[M+Cl37]1-","[2M-H]1-"),
-                         p = c('[M+H]1+','[M+K]1+','[M+Na]1+','[M+K41]1+',
-                               '[M+NH4]1+','[M+2H]2+','[2M+H]1+')),
-          transformations = transformations()$`MF Change`,
-          adductRules = adducts(),
-          isotopeRules = isotopes(),
-          transformationRules = transformations(),
-          nCores = detectCores(),
-          clusterType = 'FORK'
+          RTwindow = 1/60
       )
     }
     if (technique == 'NP-LC') {
       p <- new('AssignmentParameters',
                technique = 'NP-LC',
-               correlations = list(method = 'pearson',pAdjustMethod = 'bonferroni',corPvalue = 0.05),
-               filter = list(rthresh = 0.7,n = 100000,rIncrement = 0.01,nIncrement = 20000),
-               maxM = 600,
-               maxMFscore = 5,
-               ppm = 5,
-               limit = 0.001,
-               RTwindow = 1/60,
-               isotopes = c('13C','18O','13C2'),
-               adducts = list(n = c('[M-H]1-','[M+Hac-H]1-','[M-2H]2-','[2M-H]1-'),
-                              p = c('[M+H]1+','[M+NH4]1+','[M+H-H2O]1+','[M+ACN+H]1+','[M+Na]1+','[M+2H]2+','[2M+H]1+')),
-               transformations = transformations()$`MF Change`,
-               adductRules = adducts(),
-               isotopeRules = isotopes(),
-               transformationRules = transformations(),
-               nCores = detectCores(),
-               clusterType = 'FORK'
+               RTwindow = 1/60
       )
     }
-    if (.Platform$OS.type == 'windows') {
-      p@clusterType <- 'PSOCK'
-    }
-    p@nCores <- {detectCores() * 0.75} %>% round()
   }
   return(p)
 }