inst/doc/mouse_bioconductor.R

In ViSEAGO: ViSEAGO: a Bioconductor package for clustering biological functions using Gene Ontology and semantic similarity

## ----setup,include=FALSE------------------------------------------------------
# load ViSEAGO and mouse db package
library(ViSEAGO)

# knitr document options
knitr::opts_chunk$set(
    eval=FALSE,echo=TRUE,fig.pos = 'H',
    fig.width=6,message=FALSE,comment=NA,warning=FALSE
)

## ----vignette_data_used,eval=TRUE---------------------------------------------
# load vignette data
data(
    myGOs,
    package="ViSEAGO"
)

## ----geneList_input,eval=TRUE-------------------------------------------------
# load genes identifiants (GeneID,ENS...) background (expressed genes) 
background<-scan(
    system.file(
        "extdata/data/input",
        "background_L.txt",
        package = "ViSEAGO"
    ),
    quiet=TRUE,
    what=""
)

# load Differentialy Expressed (DE) gene identifiants from lists
PregnantvsLactateDE<-scan(
    system.file(
        "extdata/data/input",
        "pregnantvslactateDE.txt",
        package = "ViSEAGO"
    ),
    quiet=TRUE,
    what=""
)

VirginvsLactateDE<-scan(
    system.file(
        "extdata/data/input",
        "virginvslactateDE.txt",
        package = "ViSEAGO"
    ),
    quiet=TRUE,
    what=""
)

VirginvsPregnantDE<-scan(
    system.file(
        "extdata/data/input",
        "virginvspregnantDE.txt",
        package = "ViSEAGO"
    ),
    quiet=TRUE,
    what=""
)

## ----geneList_input-head,echo=FALSE-------------------------------------------
#  # show the ten first lines of genes_DE (same as genes_ref)
#  head(PregnantvsLactateDE)

## ----Genomic-ressources-------------------------------------------------------
#  # connect to Bioconductor
#  Bioconductor<-ViSEAGO::Bioconductor2GO()
#  
#  # load GO annotations from Bioconductor
#  myGENE2GO<-ViSEAGO::annotate(
#      "org.Mm.eg.db",
#      Bioconductor
#  )

## ----Genomic-ressources_show--------------------------------------------------
#  # display summary
#  myGENE2GO

## ----Genomic-ressources_display,echo=FALSE,eval=TRUE--------------------------
cat(
"- object class: gene2GO
- database: Bioconductor
- stamp/version: 2019-Jul10
- organism id: org.Mm.eg.db

GO annotations:
- Molecular Function (MF): 22707 annotated genes with 91986 terms (4121 unique terms)
- Biological Process (BP): 23210 annotated genes with 164825 terms (12224 unique terms)
- Cellular Component (CC): 23436 annotated genes with 107852 terms (1723 unique terms)"
)

## ----Enrichment_data----------------------------------------------------------
#  # create topGOdata for BP for each list of DE genes
#  BP_PregnantvsLactate<-ViSEAGO::create_topGOdata(
#      geneSel=PregnantvsLactateDE,
#      allGenes=background,
#      gene2GO=myGENE2GO,
#      ont="BP",
#      nodeSize=5
#  )
#  
#  BP_VirginvsLactate<-ViSEAGO::create_topGOdata(
#      geneSel=VirginvsLactateDE,
#      allGenes=background,
#      gene2GO=myGENE2GO,
#      ont="BP",
#      nodeSize=5
#  )
#  
#  BP_VirginvsPregnant<-ViSEAGO::create_topGOdata(
#      geneSel=VirginvsPregnantDE,
#      allGenes=background,
#      gene2GO=myGENE2GO,
#      ont="BP",
#      nodeSize=5
#  )

## ----Enrichment_data_tests----------------------------------------------------
#  # perform topGO tests
#  elim_BP_PregnantvsLactate<-topGO::runTest(
#      BP_PregnantvsLactate,
#      algorithm ="elim",
#      statistic = "fisher",
#      cutOff=0.01
#  )
#  
#  elim_BP_VirginvsLactate<-topGO::runTest(
#      BP_VirginvsLactate,
#      algorithm ="elim",
#      statistic = "fisher",
#      cutOff=0.01
#  )
#  
#  elim_BP_VirginvsPregnant<-topGO::runTest(
#      BP_VirginvsPregnant,
#      algorithm ="elim",
#      statistic = "fisher",
#      cutOff=0.01
#  )

## ----Enrichment_merge---------------------------------------------------------
#  # merge topGO results
#  BP_sResults<-ViSEAGO::merge_enrich_terms(
#      cutoff=0.01,
#      Input=list(
#          PregnantvsLactate=c(
#              "BP_PregnantvsLactate",
#              "elim_BP_PregnantvsLactate"
#          ),
#          VirginvsLactate=c(
#              "BP_VirginvsLactate",
#              "elim_BP_VirginvsLactate"
#          ),
#          VirginvsPregnant=c(
#              "BP_VirginvsPregnant",
#              "elim_BP_VirginvsPregnant"
#          )
#      )
#  )

## ----Enrichment_merge_show----------------------------------------------------
#  # display a summary
#  BP_sResults

## ----Enrichment_merge_display,echo=FALSE,eval=TRUE----------------------------
cat(
"- object class: enrich_GO_terms
- ontology: BP
- method: topGO
- summary:PregnantvsLactate
      BP_PregnantvsLactate 
        description: Bioconductor org.Mm.eg.db 2019-Jul10
        available_genes: 15804
        available_genes_significant: 7699
        feasible_genes: 14091
        feasible_genes_significant: 7044
        genes_nodeSize: 5
        nodes_number: 8463
        edges_number: 19543
      elim_BP_PregnantvsLactate 
        description: Bioconductor org.Mm.eg.db 2019-Jul10 
        test_name: fisher p<0.01
        algorithm_name: elim
        GO_scored: 8463
        GO_significant: 199
        feasible_genes: 14091
        feasible_genes_significant: 7044
        genes_nodeSize: 5
        Nontrivial_nodes: 8433 
 VirginvsLactate
      BP_VirginvsLactate 
        description: Bioconductor org.Mm.eg.db 2019-Jul10
        available_genes: 15804
        available_genes_significant: 9583
        feasible_genes: 14091
        feasible_genes_significant: 8734
        genes_nodeSize: 5
        nodes_number: 8463
        edges_number: 19543
      elim_BP_VirginvsLactate 
        description: Bioconductor org.Mm.eg.db 2019-Jul10 
        test_name: fisher p<0.01
        algorithm_name: elim
        GO_scored: 8463
        GO_significant: 152
        feasible_genes: 14091
        feasible_genes_significant: 8734
        genes_nodeSize: 5
        Nontrivial_nodes: 8457 
 VirginvsPregnant
      BP_VirginvsPregnant 
        description: Bioconductor org.Mm.eg.db 2019-Jul10
        available_genes: 15804
        available_genes_significant: 7302
        feasible_genes: 14091
        feasible_genes_significant: 6733
        genes_nodeSize: 5
        nodes_number: 8463
        edges_number: 19543
      elim_BP_VirginvsPregnant 
        description: Bioconductor org.Mm.eg.db 2019-Jul10 
        test_name: fisher p<0.01
        algorithm_name: elim
        GO_scored: 8463
        GO_significant: 243
        feasible_genes: 14091
        feasible_genes_significant: 6733
        genes_nodeSize: 5
        Nontrivial_nodes: 8413 
 
- enrichment pvalue cutoff:
        PregnantvsLactate : 0.01
        VirginvsLactate : 0.01
        VirginvsPregnant : 0.01
- enrich GOs (in at least one list): 521 GO terms of 3 conditions.
        PregnantvsLactate : 199 terms
        VirginvsLactate : 152 terms
        VirginvsPregnant : 243 terms"
)

## ----Enrichment_merge_table---------------------------------------------------
#  # show table in interactive mode
#  ViSEAGO::show_table(BP_sResults)

## ----Enrichment_merge_count---------------------------------------------------
#  # barchart of significant (or not) GO terms by comparison
#  ViSEAGO::GOcount(BP_sResults)

## ----Enrichment_merge_interactions--------------------------------------------
#  # display intersections
#  ViSEAGO::Upset(
#      BP_sResults,
#      file="upset.xls"
#  )

## ----SS_build-----------------------------------------------------------------
#  # create GO_SS-class object
#  myGOs<-ViSEAGO::build_GO_SS(
#      gene2GO=myGENE2GO,
#      enrich_GO_terms=BP_sResults
#  )

## ----SS_compute---------------------------------------------------------------
#  # compute Semantic Similarity (SS)
#  myGOs<-ViSEAGO::compute_SS_distances(
#      myGOs,
#      distance="Wang"
#  )

## ----SS_build_compute_show----------------------------------------------------
#  # display a summary
#  myGOs

## ----SS_build_compute_display,echo=FALSE,eval=TRUE----------------------------
cat(
"- object class: GO_SS
- ontology: BP
- method: topGO
- summary:
PregnantvsLactate
      BP_PregnantvsLactate 
        description: Bioconductor org.Mm.eg.db 2019-Jul10
        available_genes: 15804
        available_genes_significant: 7699
        feasible_genes: 14091
        feasible_genes_significant: 7044
        genes_nodeSize: 5
        nodes_number: 8463
        edges_number: 19543
      elim_BP_PregnantvsLactate 
        description: Bioconductor org.Mm.eg.db 2019-Jul10 
        test_name: fisher p<0.01
        algorithm_name: elim
        GO_scored: 8463
        GO_significant: 199
        feasible_genes: 14091
        feasible_genes_significant: 7044
        genes_nodeSize: 5
        Nontrivial_nodes: 8433 
 VirginvsLactate
      BP_VirginvsLactate 
        description: Bioconductor org.Mm.eg.db 2019-Jul10
        available_genes: 15804
        available_genes_significant: 9583
        feasible_genes: 14091
        feasible_genes_significant: 8734
        genes_nodeSize: 5
        nodes_number: 8463
        edges_number: 19543
      elim_BP_VirginvsLactate 
        description: Bioconductor org.Mm.eg.db 2019-Jul10 
        test_name: fisher p<0.01
        algorithm_name: elim
        GO_scored: 8463
        GO_significant: 152
        feasible_genes: 14091
        feasible_genes_significant: 8734
        genes_nodeSize: 5
        Nontrivial_nodes: 8457 
 VirginvsPregnant
      BP_VirginvsPregnant 
        description: Bioconductor org.Mm.eg.db 2019-Jul10
        available_genes: 15804
        available_genes_significant: 7302
        feasible_genes: 14091
        feasible_genes_significant: 6733
        genes_nodeSize: 5
        nodes_number: 8463
        edges_number: 19543
      elim_BP_VirginvsPregnant 
        description: Bioconductor org.Mm.eg.db 2019-Jul10 
        test_name: fisher p<0.01
        algorithm_name: elim
        GO_scored: 8463
        GO_significant: 243
        feasible_genes: 14091
        feasible_genes_significant: 6733
        genes_nodeSize: 5
        Nontrivial_nodes: 8413 
 - enrichment pvalue cutoff:
        PregnantvsLactate : 0.01
        VirginvsLactate : 0.01
        VirginvsPregnant : 0.01
- enrich GOs (in at least one list): 521 GO terms of 3 conditions.
        PregnantvsLactate : 199 terms
        VirginvsLactate : 152 terms
        VirginvsPregnant : 243 terms
- terms distances:  Wang"
)

## ----SS_terms_mdsplot---------------------------------------------------------
#  # MDSplot
#  ViSEAGO::MDSplot(myGOs)

## ----SS_Wang-wardD2-----------------------------------------------------------
#  # Create GOterms heatmap
#  Wang_clusters_wardD2<-ViSEAGO::GOterms_heatmap(
#      myGOs,
#      showIC=FALSE,
#      showGOlabels =FALSE,
#      GO.tree=list(
#          tree=list(
#              distance="Wang",
#              aggreg.method="ward.D2"
#          ),
#          cut=list(
#              dynamic=list(
#                  pamStage=TRUE,
#                  pamRespectsDendro=TRUE,
#                  deepSplit=2,
#                  minClusterSize =2
#              )
#          )
#      ),
#      samples.tree=NULL
#  )

## ----SS_Wang-wardD2_heatmap_display-------------------------------------------
#  # display the heatmap
#  ViSEAGO::show_heatmap(
#      Wang_clusters_wardD2,
#      "GOterms"
#  )

## ----SS_Wang-ward.D2_table----------------------------------------------------
#  # display table
#  ViSEAGO::show_table(
#      Wang_clusters_wardD2
#  )

## ----SS_Wang-ward.D2_mdsplot--------------------------------------------------
#  # colored MDSplot
#  ViSEAGO::MDSplot(
#      Wang_clusters_wardD2,
#      "GOterms"
#  )

## ----SS_Wang-wardD2_groups----------------------------------------------------
#  # calculate semantic similarites between clusters of GO terms
#  Wang_clusters_wardD2<-ViSEAGO::compute_SS_distances(
#      Wang_clusters_wardD2,
#      distance="BMA"
#  )

## ----SS_Wang-ward.D2_groups_mdsplot-------------------------------------------
#  # MDSplot
#  ViSEAGO::MDSplot(
#      Wang_clusters_wardD2,
#      "GOclusters"
#  )

## ----SS_Wang-wardD2_groups_heatmap--------------------------------------------
#  # GOclusters heatmap
#  Wang_clusters_wardD2<-ViSEAGO::GOclusters_heatmap(
#      Wang_clusters_wardD2,
#      tree=list(
#          distance="BMA",
#          aggreg.method="ward.D2"
#      )
#  )

## ----SS_Wang-ward.D2_groups_heatmap_display-----------------------------------
#  # display the heatmap
#  ViSEAGO::show_heatmap(
#      Wang_clusters_wardD2,
#      "GOclusters"
#  )

## ----SS_Wang-wardD2_groups_show-----------------------------------------------
#  # display a summary
#  Wang_clusters_wardD2

## ----SS_Wang-wardD2_groups_display,echo=FALSE,eval=TRUE-----------------------
cat(
"- object class: GO_clusters
- ontology: BP
- method: topGO
- summary:
PregnantvsLactate
      BP_PregnantvsLactate 
        description: Bioconductor org.Mm.eg.db 2019-Jul10
        available_genes: 15804
        available_genes_significant: 7699
        feasible_genes: 14091
        feasible_genes_significant: 7044
        genes_nodeSize: 5
        nodes_number: 8463
        edges_number: 19543
      elim_BP_PregnantvsLactate 
        description: Bioconductor org.Mm.eg.db 2019-Jul10 
        test_name: fisher p<0.01
        algorithm_name: elim
        GO_scored: 8463
        GO_significant: 199
        feasible_genes: 14091
        feasible_genes_significant: 7044
        genes_nodeSize: 5
        Nontrivial_nodes: 8433 
 VirginvsLactate
      BP_VirginvsLactate 
        description: Bioconductor org.Mm.eg.db 2019-Jul10
        available_genes: 15804
        available_genes_significant: 9583
        feasible_genes: 14091
        feasible_genes_significant: 8734
        genes_nodeSize: 5
        nodes_number: 8463
        edges_number: 19543
      elim_BP_VirginvsLactate 
        description: Bioconductor org.Mm.eg.db 2019-Jul10 
        test_name: fisher p<0.01
        algorithm_name: elim
        GO_scored: 8463
        GO_significant: 152
        feasible_genes: 14091
        feasible_genes_significant: 8734
        genes_nodeSize: 5
        Nontrivial_nodes: 8457 
 VirginvsPregnant
      BP_VirginvsPregnant 
        description: Bioconductor org.Mm.eg.db 2019-Jul10
        available_genes: 15804
        available_genes_significant: 7302
        feasible_genes: 14091
        feasible_genes_significant: 6733
        genes_nodeSize: 5
        nodes_number: 8463
        edges_number: 19543
      elim_BP_VirginvsPregnant 
        description: Bioconductor org.Mm.eg.db 2019-Jul10 
        test_name: fisher p<0.01
        algorithm_name: elim
        GO_scored: 8463
        GO_significant: 243
        feasible_genes: 14091
        feasible_genes_significant: 6733
        genes_nodeSize: 5
        Nontrivial_nodes: 8413 
 - enrichment pvalue cutoff:
        PregnantvsLactate : 0.01
        VirginvsLactate : 0.01
        VirginvsPregnant : 0.01
- enrich GOs (in at least one list): 521 GO terms of 3 conditions.
        PregnantvsLactate : 199 terms
        VirginvsLactate : 152 terms
        VirginvsPregnant : 243 terms
- terms distances:  Wang
- clusters distances: BMA
- Heatmap:
          * GOterms: TRUE
                    - GO.tree:
                              tree.distance: Wang
                              tree.aggreg.method: ward.D2
                              cut.dynamic.pamStage: TRUE
                              cut.dynamic.pamRespectsDendro: TRUE
                              cut.dynamic.deepSplit: 2
                              cut.dynamic.minClusterSize: 2
                              number of clusters: 62
                              clusters min size: 2
                              clusters mean size: 8
                              clusters max size: 32
                   - sample.tree: FALSE
          * GOclusters: TRUE
                       - tree:
                              distance: BMA
                              aggreg.method: ward.D2"
)

## ----session,eval=TRUE,echo=FALSE---------------------------------------------
sessionInfo()