I am using registerDoParallel(2) to run some analysis in parallel using foreach and %dopar%. However I can't manage to calculate in parallel one thing I can calculate in sequential order.

The function I want to use in parallel is this one:

# Calculates the degree of overlap of the GO BP ontologies of entrez ids.
go_cor <- function(e_a, e_b, chip = "hgu133plus2.db", mapfun = NULL,
                   Ontology = "BP", ...) {
  # https://support.bioconductor.org/p/85702/#85732

  if (is.na(e_a) | is.na(e_b)) {
    return(NA)
  }
  # Ensure proper format
  e_a <- as.character(e_a)
  e_b <- as.character(e_b)

  if (mapfun) {
    mapfunc <- function(z) {
      mget(z, revmap(org.Hs.egGO2EG), ifnotfound = NA)
    }

    LP <- simLL(e_a, e_b, Ontology, measure = "LP", mapfun = mapfunc)
    UI <- simLL(e_a, e_b, Ontology, measure = "UI", mapfun = mapfunc)
  } else {
    LP <- simLL(e_a, e_b, Ontology, measure = "LP", chip = chip)
    UI <- simLL(e_a, e_b, Ontology, measure = "UI", chip = chip)
  }
  out <- NA
  if (length(LP) > 1 | length(UI) > 1) {
    if (is.na(LP["sim"]) | is.na(UI["sim"])) {
      return(NA)
    } else {
      mean.g1 <- s.path(LP$g1)
      mean.g2 <- s.path(LP$g2)
      out <- (UI$sim/LP$sim)*max(mean.g1, mean.g2,na.rm = T)
      return(out)
    }
  } else if (is.na(LP) | is.na(UI)) {
    return(out)
  }
  return(out)
}

s.path <- function(ig){
  lfi <- graph::leaves(ig, "in")
  degs <- graph::degree(ig)
  root <- names(degs$outDegree)[degs$outDegree == 0]
  paths <- RBGL::sp.between(ig, lfi, root)
  plens <- Biobase::subListExtract(paths, "length", simplify = TRUE)
  out <- max(plens)
}

This code is called with code similar to:

comb <-list(c("12", "28"), c("12", "52"), c("12", "159"), c("12", "175"
), c("12", "280"), c("28", "52"), c("28", "159"), c("28", "175"
), c("28", "280"), c("52", "159"), c("52", "175"), c("52", "280"
), c("159", "175"), c("159", "280"), c("175", "280"))

go.mat <- foreach(i = seq_len(length(comb)),
                  .combine = c, verbose = TRUE) %dopar% {
    ## message("new comb ", paste(comb))
    combi <- comb[i]
    go_cor(combi[1], combi[2], mapfun = TRUE, Ontology = "BP")
}

When I use %dopar% or %do% with registerDoSEQ() I just get the first score, but when I use a for loop it calculates more than one score `for (i in 1:length(comb){....}`.

Is there anything on the Bioconductor packages I use inside go_cor function that prevents me to running it on parallel? I thought it could be due to not loading the right libraries, on the workers, but I used the `.package =  c("org.Hs.eg.db", "RBGL", "Rgraphviz", "graph", "Biobase", "AnnotationDbi")` and still it didn't work. By didn't work I mean I get no error neither message of why it is failing, just one plain value in go.mat and nothing else.

> sessionInfo()
R version 3.2.3 (2015-12-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 14.04.2 LTS

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=es_ES.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=es_ES.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=es_ES.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=es_ES.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
 [1] grid      stats4    parallel  stats     graphics  grDevices utils    
 [8] datasets  methods   base     

other attached packages:
 [1] topGO_2.22.0         SparseM_1.72         Rgraphviz_2.14.0    
 [4] RBGL_1.46.0          org.Hs.eg.db_3.2.3   GOstats_2.36.0      
 [7] graph_1.48.0         Category_2.36.0      GO.db_3.2.2         
[10] RSQLite_1.0.0        DBI_0.5-1            AnnotationDbi_1.32.3
[13] IRanges_2.4.8        S4Vectors_0.8.11     Matrix_1.2-7.1      
[16] Biobase_2.30.0       BiocGenerics_0.16.1  doParallel_1.0.10   
[19] iterators_1.0.8      foreach_1.4.3        BiocParallel_1.4.3  

loaded via a namespace (and not attached):
 [1] splines_3.2.3          xtable_1.8-2           lattice_0.20-34       
 [4] tools_3.2.3            AnnotationForge_1.12.2 genefilter_1.52.1     
 [7] lambda.r_1.1.9         futile.logger_1.4.3    survival_2.39-5       
[10] GSEABase_1.32.0        futile.options_1.0.0   codetools_0.2-15      
[13] XML_3.98-1.4           annotate_1.48.0      

> registered()
$MulticoreParam
class: MulticoreParam
  bpjobname:BPJOB; bpworkers:10; bptasks:0; bptimeout:Inf; bpRNGseed:; bpisup:FALSE
  bplog:FALSE; bpthreshold:INFO; bplogdir:NA
  bpstopOnError:FALSE; bpprogressbar:FALSE
  bpresultdir:NA
cluster type: FORK

$SnowParam
class: SnowParam
  bpjobname:BPJOB; bpworkers:10; bptasks:0; bptimeout:Inf; bpRNGseed:; bpisup:FALSE
  bplog:FALSE; bpthreshold:INFO; bplogdir:NA
  bpstopOnError:FALSE; bpprogressbar:FALSE
  bpresultdir:NA
cluster type: SOCK

$SerialParam
class: SerialParam
  bplog:FALSE; bpthreshold:INFO
  bpcatchErrors:FALSE

EDIT: After some modifications (per Mike answer) I can see all the iterations but there is an error in

task 2 failed - "rsqlite_query_fetch: failed first step: database disk image is malformed"

I made your example as minimal as possible by removing parts until I had just what was needed to reproduce the error

suppressPackageStartupMessages({
    library("GOstats")
    library("org.Hs.eg.db")

    library("foreach")
    library("doParallel")
    registerDoParallel()
})

go_cor <- function(e_a, e_b) {
    mapfunc <- function(z)
        mget(z, revmap(org.Hs.egGO2EG), ifnotfound = NA)
    simLL(e_a, e_b, "BP", measure = "LP", mapfun = mapfunc)
}

comb <- list(c("12", "28"), c("12", "52"), c("12", "159"), c("12", "175"),
    c("12", "280"), c("28", "52"), c("28", "159"), c("28", "175"),
    c("28", "280"), c("52", "159"), c("52", "175"), c("52", "280"),
    c("159", "175"), c("159", "280"), c("175", "280"))

foreach(combi = comb) %dopar%
    go_cor(combi[1], combi[2])

I agree with Robert that the likely problem is that multiple threads are using the same database connection, and I tried to solve this by loading the data base packages in the workers only

suppressPackageStartupMessages({
    library("foreach")
    library("doParallel")
    registerDoParallel()
})

go_cor <- function(e_a, e_b) {
    suppressPackageStartupMessages({
        library("GOstats")
        library("org.Hs.eg.db")
    })
    mapfunc <- function(z)
        mget(z, revmap(org.Hs.egGO2EG), ifnotfound = NA)
    simLL(e_a, e_b, "BP", measure = "LP", mapfun = mapfunc)
}

comb <- list(c("12", "28"), c("12", "52"), c("12", "159"), c("12", "175"),
    c("12", "280"), c("28", "52"), c("28", "159"), c("28", "175"),
    c("28", "280"), c("52", "159"), c("52", "175"), c("52", "280"),
    c("159", "175"), c("159", "280"), c("175", "280"))

foreach(combi = comb) %dopar%
    go_cor(combi[1], combi[2])

This seems to work.

A couple of thoughts on this bit of code

go.mat <- foreach(i = seq_len(length(comb),
                      .combine = c, verbose = TRUE) %dopar% {
                        # message("new comb ", paste(comb))
                        combi <- comb[i]
                        go_cor(combi[1], combi[2], mapfun = TRUE, Ontology = "BP")
                      }

Are you missing a bracket to close seq_len() before the .combine? Also the verbose argument to foreach() has a period before it e.g. .verbose = TRUE. I think without that you're passing verbose into the evaluation environment and that may be influencing how many times it is executed.

Does this work any better?

go.mat <- foreach(i = seq_len(length(comb)),
                  .combine = c,
                  .verbose = TRUE) %dopar% {
                      # message("new comb ", paste(comb))
                      combi <- comb[i]
                      go_cor(combi[1], combi[2], mapfun = TRUE, Ontology = "BP")
                  }