Package 'DEsubs'

Default run of DEsubs

Description

Default run of DEsubs

Usage

DEsubs(org, mRNAexpr, mRNAnomenclature, pathways, DEtool, DEpar,
    CORtool, CORpar, subpathwayType, rankedList, verbose)

Arguments

org	Organism identifier ('hsa', 'mmu', 'rno', 'sce', 'ath', 'dme', 'dre')
mRNAexpr	RNA-seq expression data in the form of either a matrix or a filename of a text file stored in the 'User' directory.
mRNAnomenclature	mRNAnomenclature ('entrezgene', 'ensembl_gene_id', 'ensembl_transcript_id', 'ensembl_peptide_id', 'hgnc_id', 'hgnc_symbol', 'hgnc_transcript_name', 'refseq_mrna', 'refseq_peptide')
pathways	Pathway type ('All', 'Non-Metabolic', 'Metabolic')
DEtool	DEG analysis tool selection for NodeRule ('edgeR', 'DESeq2', 'EBSeq', 'NBPSeq', 'voom+limma', 'vst2+limma', 'TSPM')
DEpar	DE analysis tools Q-value threshold of NodeRule (default: DEGpar = 0.05)
CORtool	Correlation measure selection for EdgeRule ('pearson', 'kendall', 'spearman')
CORpar	Correlation measure threshold of EdgeRule (default: CORpar = 0.6)
subpathwayType	Subpathway extraction type selection (get all availiable options from subpathwayTypes)
rankedList	A named vector of genes and their corresponding significance of differential expression in the form of a Q-value. If the argument is not null, no DEtool is used for differential expression analysis.
verbose	TRUE to display informative messages, FALSE to hide.

Details

• Class vector needed values 1 and 2 for each class (eg. control and disease samples).

• DEpar should be less than 0.05 in order to return statistically significant DEGs.

• Higher CORpar values result in stricter correlation criteria, i.e. less acceptable interactions.

Value

A list used as input in geneVisualization, subpathwayVisualization, subpathwayToGraph, organismVisualization

Examples

load(system.file('extdata', 'data.RData', package='DEsubs'))

DEsubs.run <- DEsubs(   org='hsa', 
                        mRNAexpr=mRNAexpr, 
                        mRNAnomenclature='entrezgene', 
                        pathways='All', 
                        DEtool=NULL, DEpar=0.05,
                        CORtool='pearson', CORpar=0.6, 
                        subpathwayType=NULL,
                        rankedList=rankedList)

---

Gene level visualization

Description

Visualizes topologically and functionally significant genes using graph theory measures as well as their correlation to pathway, disease, drug, ontology, microRNA and Transcription Factor terms based on external references.

Usage

geneVisualization(DEsubs.out, measures.topological, measures.functional, 
    measures.barplot, topGenes, colors.topological, colors.functional, 
    colors.barplot, size.topological, size.functional, size.barplot, 
    outfile.topological, outfile.functional, outfile.barplot,
    export, verbose)

Arguments

DEsubs.out	Return value from DEsubs
measures.topological	Functional visualization type(s).
measures.functional	Topological visualization type(s).
measures.barplot	Gene level Visualization type
topGenes	Number of genes with greater Q-values. Default value is 10.
colors.topological	A custom color mode which overrrides the default settings.
colors.functional	A custom color mode which overrrides the default settings.
colors.barplot	A custom color mode which overrrides the default settings.
size.topological	A vector storing width and height of the topological measures visualization
size.functional	A vector storing width and height of the functional measures visualization
size.barplot	A vector storing width and height of the barplot visualization
outfile.topological	Output file name of the topological measures visualization.
outfile.functional	Output file name of the functional measures visualization.
outfile.barplot	Output file name of the barplot visualization.
export	Export type of visualizations ('plot', 'pdf')
verbose	TRUE to display informative messages, FALSE to hide.

Details

• Topological visualization type contains six topological graph theory measures, namely degree, betweeness centrality, closeness centrality, hub_score, eccentricity and page_rank. The availiable options are 'degree', 'betweenness', 'closeness', 'hub_score', 'eccentricity' and 'page_rank'. If no argument is supplied, all availiable options are selected by default. If the argument is NULL, no visualization is exported.

• Functional visualization type contains associations with (i) KEGG's pathway terms, (ii) Gene Ontologies of Molecular function, biological processes and cellular components) (iii) Disease terms from OMIM and GAD databases), (iv) Drug substances from DrugBank) and the influence of (v) microRNA targets from miRecords and (vi) Transcription Factor targets from Transfac and Jaspar. The availiable options are 'KEGG', 'GO_bp', 'GO_cc', 'GO_mf', 'Disease_OMIM' , 'Disease_GAD', 'Drug_DrugBank', 'miRNA' and 'TF'. If no argument is supplied, all availiable options are selected by default. If the argument is NULL, no visualization is exported. Using option 'all' results in the selection of all afforementioned options, along with any other custom gene sets within the 'DEsubs/Data' user specified-directory.

Value

Individual measure results in matrix form.

Examples

load(system.file('extdata', 'data.RData', package='DEsubs'))

outfile.topological <- tempfile(fileext='.pdf') 
outfile.functional <- tempfile(fileext='.pdf') 
outfile.barplot <- tempfile(fileext='.pdf') 

res <- geneVisualization(  
            DEsubs.out=DEsubs.out, top=10,
            measures.topological=c( 'degree', 'betweenness', 'closeness',
                                    'eccentricity', 'page_rank'),
            measures.functional=c(  'KEGG', 
                                    'Disease_OMIM', 'Disease_GAD', 
                                    'Drug_DrugBank','miRNA', 'TF'),
            size.topological=c(5,4),
            size.functional=c(7,4),
            size.barplot=c(5,6),
            export='pdf',
            outfile.topological=outfile.topological,
            outfile.functional=outfile.functional,
            outfile.barplot=outfile.barplot,
            verbose=FALSE)

---

Organism level visualization

Description

Organism level measures

Usage

organismVisualization( DEsubs.out, references, topSubs, topTerms, colors,
                        export, width, height, outfiles, verbose )

Arguments

DEsubs.out	Return value from DEsubs
references	Functional associations with (i) KEGG's pathway terms, (ii) Gene Ontologies of Molecular function, biological processes and cellular components) (iii) Disease terms from OMIM and GAD databases), (iv) Drug substances from DrugBank) and the influence of (v) microRNA targets from miRecords and (vi) Transcription Factor targets from Transfac and Jaspar. The corresponding options are 'KEGG', 'GO_bp', 'GO_cc', 'GO_mf', 'Disease_OMIM' , 'Disease_GAD', 'Drug_DrugBank', 'miRNA' and 'TF'. If no argument is supplied, no option is selected. Using option 'all' results in the selection of all afforementioned options, along with any other custom gene sets within the 'DEsubs/Data' user specified-directory.
topSubs	Default value is 10
topTerms	Default value is 20
colors	A custom color mode which overrides the default settings.
export	Export type of visualizations ('plot', 'pdf')
width	The width of the printable area (pdf)
height	The height of the printable area (pdf)
outfiles	Output filenames of the visualizations. If the argument is not specified, default filenames are used ('DEsubs/Output').
verbose	TRUE to display informative messages, FALSE to hide.

Value

A list of matrices, containing Subpathway/Term/P-Value results for each reference.

Examples

load(system.file('extdata', 'data.RData', package='DEsubs'))

outfile <- tempfile(fileext='.pdf')  

res <- organismVisualization( 
                DEsubs.out=DEsubs.out, references='KEGG', 
                topSubs=10, topTerms=20,
                width=7, height=6,
                export='pdf', 
                outfile=outfile,
                verbose=FALSE)

---

Subpathway To Graph

Description

Subpathway plotting as a graph.

Usage

subpathwayToGraph( DEsubs.out, submethod, subname, colors, size, export, 
                    width, height, outfile, verbose )

Arguments

DEsubs.out	Return value from DEsubs
submethod	Subpathway extraction type selection (get all availiable options from subpathwayTypes)
subname	Subpathway name as contained in DEsubs return value, i.e. 'sub1'.
colors	A custom color mode which overrides the default settings.
size	A vector storing width and height of the barplot visualization.
export	A set of options for exporting subpathway data. Possible options are 'plot', 'pdf', 'edgelist', 'json', 'gml', 'ncol', 'lgl', 'graphml','dot'.
width	The width of the printable area (pdf)
height	The height of the printable area (pdf)
outfile	Output file name of the visualization. If multiple export types have been selected, the outfile should have an extension '.*'
verbose	TRUE to display informative messages, FALSE to hide.

Value

No value is returned.

Examples

load(system.file('extdata', 'data.RData', package='DEsubs'))

outfile <- tempfile(fileext='.pdf')  

res <- subpathwayToGraph( 
                DEsubs.out=DEsubs.out, 
                submethod='community.walktrap', 
                subname=paste0('sub', 6),
                size=c(10,10),
                export='pdf',
                outfile=outfile )

---

All subpathway types

Description

All subpathway types.

Usage

subpathwayTypes(grouping)

Arguments

grouping

By supplying one of the availiable groupings, specific subsets of availiable subpathway types can be extracted.

Details

Apart from the 124 distinct subpathway types, several groupings are availiable:

'all'

All subpathway options.

'all.bwd'

Forward propagation.

'all.fwd'

Backward propagation.

'all.stream'

All possible genes targeting or are targeted via a path starting from a gene of interest.

'all.neighbourhood'

All adjacent genes of a gene of interest with incoming or outgoing links.

'all.cascade'

A finite sequence of interactions connecting a sequence of genes starting or ending from a gene of interest.

'all.community'

Group of genes sharing common properties.

'all.component'

Subgraphs on which any two vertices are (strongly) connected to each other by paths.

'all.functional'

Forward and backward streams starting from genes/nodes with crucial functional role within the network. Individual options include GO_bp, GO_cc, GO_mf, KEGG, Disease_OMIM, Disease_GAD, Drug_DrugBank, miRNA, TF, DEG, which are defined below.

'all.GO_bp'

Genes acting as a bridge among Gene Ontology (GO) Biological Process terms.

'all.GO_cc'

Genes acting as a bridge among Gene Ontology (GO) Cellular Component terms.

'all.GO_mf'

Genes acting as a bridge among Gene Ontology (GO) Molecular Function terms.

'all.KEGG'

Genes acting as a bridge among KEGG pathway maps.

'all.Disease_OMIM'

Genes acting as a bridge among OMIM Disease targets.

'all.Disease_GAD'

Genes acting as a bridge among GAD Disease targets.

'all.Drug_DrugBank'

Genes acting as a bridge among DrugBank Drug targets.

'all.miRNA'

Genes acting as a bridge among microRNA-gene targets.

'all.TF'

Genes acting as a bridge among TF-gene targets.

'all.DEG'

Genes with highly Differentially expressed by each experimental data.

'all.topological'

Forward and backward streams starting from genes/nodes with crucial topological role within the network. Individual options include degree, betweenness, closeness, hub_score, eccentricity, page_rank, start_nodes which are defined below.

'all.degree'

Number of gene's adjacent interactions.

'all.betweenness'

Number of shortest paths from all vertices to others passing through a node.

'all.closeness'

Inverse of farness, which is the sum of distances to all other nodes.

'all.hub_score'

Kleinberg's hub centrality score.

'all.eccentricity'

Shortest path distance from the farthest other node in the graph.

'all.page_rank'

Google Page Rank.

'all.start_nodes'

Gene nodes without incoming links.

An exhaustive list of all 124 subpathway types follows:

STREAM-TOPOLOGICAL
'bwd.stream.topological.degree'	'fwd.stream.topological.degree'
'bwd.stream.topological.betweenness'	'fwd.stream.topological.betweenness'
'bwd.stream.topological.closeness'	'fwd.stream.topological.closeness'
'bwd.stream.topological.hub_score'	'fwd.stream.topological.hub_score'
'bwd.stream.topological.eccentricity'	'fwd.stream.topological.eccentricity'
'bwd.stream.topological.page_rank'	'fwd.stream.topological.page_rank'
'bwd.stream.topological.start_nodes'	'fwd.stream.topological.start_nodes'
STREAM-FUNCTIONAL
'bwd.stream.functional.GO_bp'	'fwd.stream.functional.GO_bp'
'bwd.stream.functional.GO_cc'	'fwd.stream.functional.GO_cc'
'bwd.stream.functional.GO_mf'	'fwd.stream.functional.GO_mf'
'bwd.stream.functional.KEGG'	'fwd.stream.functional.KEGG'
'bwd.stream.functional.Disease_OMIM'	'fwd.stream.functional.Disease_OMIM'
'bwd.stream.functional.Disease_GAD'	'fwd.stream.functional.Disease_GAD'
'bwd.stream.functional.Drug_DrugBank'	'fwd.stream.functional.Drug_DrugBank'
'bwd.stream.functional.miRNA'	'fwd.stream.functional.miRNA'
'bwd.stream.functional.TF'	'fwd.stream.functional.TF'
'bwd.stream.functional.DEG'	'fwd.stream.functional.DEG'
NEIGHBOURHOOD-TOPOLOGICAL
'bwd.neighbourhood.topological.degree'	'fwd.neighbourhood.topological.degree'
'bwd.neighbourhood.topological.betweenness'	'fwd.neighbourhood.topological.betweenness'
'bwd.neighbourhood.topological.closeness'	'fwd.neighbourhood.topological.closeness'
'bwd.neighbourhood.topological.hub_score'	'fwd.neighbourhood.topological.hub_score'
'bwd.neighbourhood.topological.eccentricity'	'fwd.neighbourhood.topological.eccentricity'
'bwd.neighbourhood.topological.page_rank'	'fwd.neighbourhood.topological.page_rank'
'bwd.neighbourhood.topological.start_nodes'	'fwd.neighbourhood.topological.start_nodes'
NEIGHBOURHOOD-FUNCTIONAL
'bwd.neighbourhood.functional.GO_bp'	'fwd.neighbourhood.functional.GO_bp'
'bwd.neighbourhood.functional.GO_cc'	'fwd.neighbourhood.functional.GO_cc'
'bwd.neighbourhood.functional.GO_mf'	'fwd.neighbourhood.functional.GO_mf'
'bwd.neighbourhood.functional.KEGG'	'fwd.neighbourhood.functional.KEGG'
'bwd.neighbourhood.functional.Disease_OMIM'	'fwd.neighbourhood.functional.Disease_OMIM'
'bwd.neighbourhood.functional.Disease_GAD'	'fwd.neighbourhood.functional.Disease_GAD'
'bwd.neighbourhood.functional.Drug_DrugBank'	'fwd.neighbourhood.functional.Drug_DrugBank'
'bwd.neighbourhood.functional.miRNA'	'fwd.neighbourhood.functional.miRNA'
'bwd.neighbourhood.functional.TF'	'fwd.neighbourhood.functional.DEG'
CASCADE-TOPOLOGICAL
'bwd.cascade.topological.degree'	'fwd.cascade.topological.degree'
'bwd.cascade.topological.betweenness'	'fwd.cascade.topological.betweenness'
'bwd.cascade.topological.closeness'	'fwd.cascade.topological.closeness'
'bwd.cascade.topological.hub_score'	'fwd.cascade.topological.hub_score'
'bwd.cascade.topological.eccentricity'	'fwd.cascade.topological.eccentricity'
'bwd.cascade.topological.page_rank'	'fwd.cascade.topological.page_rank'
'bwd.cascade.topological.start_nodes'	'fwd.cascade.topological.start_nodes'
CASCADE-FUNCTIONAL
'bwd.cascade.functional.GO_bp'	'fwd.cascade.functional.GO_bp'
'bwd.cascade.functional.GO_cc'	'fwd.cascade.functional.GO_cc'
'bwd.cascade.functional.GO_mf'	'fwd.cascade.functional.GO_mf'
'bwd.cascade.functional.KEGG'	'fwd.cascade.functional.KEGG'
'bwd.cascade.functional.Disease_OMIM'	'fwd.cascade.functional.Disease_OMIM'
'bwd.cascade.functional.Disease_GAD'	'fwd.cascade.functional.Disease_GAD'
'bwd.cascade.functional.Drug_DrugBank'	'fwd.cascade.functional.Drug_DrugBank'
'bwd.cascade.functional.miRNA'	'fwd.cascade.functional.miRNA'
'bwd.cascade.functional.TF'	'fwd.cascade.functional.TF'
'bwd.cascade.functional.DEG'	'fwd.cascade.functional.DEG'
COMMUNITY
'community.walktrap'	'community.edge_betweenness'
'community.fast_greedy'	'community.leading_eigen'
'community.infomap'	'community.louvain'
COMPONENT-CLIQUES
'component.max_cliques'	'component.decompose'
'component.3-cliques'	...
...	'component.9-cliques'
COMPONENT-CORENESS
'component.3-coreness'	...
...	'component.9-coreness'

Value

A vector of all 124 basic subpathway types. See Details section for handly groupings.

Examples

basic.types <- subpathwayTypes()
stream.types <- subpathwayTypes(grouping='all.stream')

---

Subpathway level visualization

Description

Circular diagrams containing subpathways enrichment in potential key regulators (miRNAs, TFs) and biological, biomedical and pharmacological issues.

Usage

subpathwayVisualization( DEsubs.out, references, submethod, subname, colors, 
                        scale, shuffleColors, outfiles, export, verbose )

Arguments

DEsubs.out	Return value from DEsubs.
references	Topological references include degree, betweeness centrality, closeness centrality, hub_score, eccentricity and page_rank. The corresponding options are 'degree', 'betweenness', 'closeness', 'hub_score', 'eccentricity' and 'page_rank'. Functional references include (i) KEGG's pathway terms, (ii) Gene Ontologies of Molecular function, biological processes and cellular components) (iii) Disease terms from OMIM and GAD databases), (iv) Drug substances from DrugBank) and the influence of (v) microRNA targets from miRecords and (vi) Transcription Factor targets from Transfac and Jaspar. The corresponding options are 'KEGG', 'GO_bp', 'GO_cc', 'GO_mf', 'Disease_OMIM' , 'Disease_GAD', 'Drug_DrugBank', 'miRNA' and 'TF'.Using option 'all' results in the selection of all afforementioned options, along with any other custom gene sets within the 'DEsubs/Data' user specified-directory.
submethod	Subpathway extraction type selection (see all 124 options along with their R commands in supplementary document)
subname	Subpathway name as contained in DEsubs return value, i.e. 'sub1'
colors	A custom color mode which overrrides the default settings.
scale	A value in (0,1] used to scale the visualization. Useful in the case of long labels which are trimmed by default.
shuffleColors	TRUE to shuffle user defined or default colors. Defaults to FALSE.
outfiles	Output filenames of the visualizations. If the argument is not specified, default filenames are used ('DEsubs/Output').
export	Export type of visualizations ('plot', 'pdf')
verbose	TRUE to display informative messages, FALSE to hide.

Details

The associations of subpathways with various biological and pharmacologicalfeatures are estimated through a hypergeometric test. The enriched associations of a subpathway to each feature are illustrated through circular diagrams.

Value

A list of matrices, each containing the P-Value of enrichment between the terms for a specific reference (rows) and each of the subpathway genes (columns). If there is no enrichment, the value is NA.

Examples

load(system.file('extdata', 'data.RData', package='DEsubs'))

outfile <- tempfile(fileext='.pdf') 

res <- subpathwayVisualization( 
                DEsubs.out=DEsubs.out,  
                references=c('TF'), 
                submethod='community.walktrap',
                subname='sub1', 
                scale=c(1.0), 
                export='pdf',
                outfile=outfile )

---