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example in Table 1 shows the right structure for RNA-seq expression data input.
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-```{r, eval=TRUE, echo=FALSE, results = 'asis'}
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-data <- c( 1879, 2734, 2369, 2636, 2188, 9743, 9932, 10099,
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- 97, 124, 146, 114, 126, 33, 19, 31,
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- 485, 485, 469, 428, 475, 128, 135, 103,
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- 84, 25, 67, 62, 61, 277, 246, 297,
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- 120, 312, 78, 514, 210, 324, 95, 102)
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-data <- matrix(data, nrow=6, ncol=8, byrow=TRUE)
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-
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-rownames(data) <- c(paste0('Gene ', 1:3), '...', 'Gene N-1', 'Gene N')
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-colnames(data) <- c(paste0('Case ', 1:4), paste0('Control ', 1:4))
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-
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-kable( data,
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- caption = 'Example of user input format' )
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-```
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+Gene Case 1 Case 2 Case 3 Case 4 Control 1 Control 2 Control 3 Control 4
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+------------------ --------- --------- --------- --------- --------- --------- --------- ---------
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+Gene 1 1879 2734 2369 2636 2188 9743 9932 10099
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+Gene 2 97 124 146 114 126 33 19 31
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+Gene 3 485 485 469 428 475 128 135 103
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+... ... ... ... ... ... ... ... ...
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+Gene N-1 84 25 67 62 61 277 246 297
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+Gene N 120 312 78 514 210 324 95 102
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+------------------ --------- --------- --------- --------- --------- --------- --------- ---------
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+Table: Example of user input format
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## 3. Pathway network construction
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KEGG signaling pathway maps have been downloaded and converted to pathway
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-networks using CHRONOS package. Pathway networks for the six supported
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+networks using CHRONOS package. Pathway networks for the seven supported
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organisms are included in the package itself (see Table 2).
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-```{r, eval=TRUE, echo=FALSE, results = 'asis'}
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-data <- c( 'Homo sapiens', "'hsa'",
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- 'Mus musculus', "'mmu'",
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- 'Drosophila melanogaster', "'dme'",
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- 'Saccharomyces cerevisiae', "'sce'",
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- 'Arabidopsis thaliana', "'ath'",
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- 'Rattus norvegicus', "'rno'",
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- 'Danio rerio', "'dre'")
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-data <- matrix(data, nrow=7, ncol=2, byrow=TRUE)
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+Supported Organisms R command
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+-------------- ----------------
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+Homo sapiens 'hsa'
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+Mus musculus 'mmu'
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+Drosophila melanogaster 'dme'
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+Saccharomyces cerevisiae 'sce'
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+Arabidopsis thaliana 'ath'
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+Rattus norvegicus 'rno'
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+Danio rerio 'dre'
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+-------------- ----------------
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+Table: Supported KEGG organisms
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-kable( data,
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- caption = 'DEsubs supported KEGG organisms' )
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-```
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DEsubs operates with Entrez ID labels, however twelve other label systems
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are supported after converting to Entrez IDs via a lexicon included in
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the package itself (see Table 3).
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-```{r, eval=TRUE, echo=FALSE, results = 'asis'}
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-
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-data <- c( 'Entrez', "'entrezgene'",
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- 'Ensemble', "'ensembl_gene_id', 'ensembl_transcript_id'",
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- '', "'ensembl_peptide_id'",
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- 'HGNC', "'hgnc_id', 'hgnc_symbol', 'hgnc_transcript_name'",
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- 'Refseq', "'refseq_mrna', 'refseq_peptide'")
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-data <- matrix(data, nrow=5, ncol=2, byrow=TRUE)
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-colnames(data) <- c('Supported Labels', 'R command')
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+Supported Labels R command
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+------------ ----------------
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+Entrez 'entrezgene'
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+Ensemble 'ensembl_gene_id', 'ensembl_transcript_id'
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+ 'ensembl_peptide_id'
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+HGNC 'hgnc_id', 'hgnc_symbol', 'hgnc_transcript_name'
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+Refseq 'refseq_mrna', 'refseq_peptide'
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+------------ ----------------
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+Table: Supported gene labels
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-kable( data,
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- caption = 'Supported gene labels' )
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-```
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\newpage
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-```{r, eval=TRUE, echo=FALSE, results = 'asis'}
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-
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-data <- c( 'Pearson product-moment correlation coefficient', "'pearson'",
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- 'Spearman rank correlation coefficient', "'spearman'",
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- 'Kendall rank correlation coefficient', "'kedhall'")
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-data <- matrix(data, nrow=3, ncol=2, byrow=TRUE)
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+Type R command
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+-------------- ----------------
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+Pearson product-moment correlation coefficient 'pearson'
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+Spearman rank correlation coefficient 'spearman'
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+Kendall rank correlation coefficient 'kedhall'
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+-------------- ----------------
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+Table: Edge Rule options
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-rownames(data) <- rep('', nrow(data))
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-colnames(data) <- c('Type', 'R command')
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-
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-kable( data,
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- caption = 'Edge Rule options' )
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-```
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-------------- ----------------
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Subpathway extraction is based on five main categories, (i) components,
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(ii) communities, (iii) streams, (iv) neighborhoods, (v) cascades. Each one
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sketches different topological aspect within the network. Indicative examples
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-and a short description of DEsubs five main subpathway categories cam be found
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+and a short description of DEsubs five main subpathway categories can be found
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in Figure 1.
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-{height=320px}
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+
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+```{r eval=TRUE, echo=FALSE, out.height='235px', fig.align='center', fig.cap=cap, fig.pos='h', out.extra=''}
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+
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+cap <- paste0(
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+ 'Stream, neighborhood and cascade types build each subpathway ',
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+ '(blue nodes) by starting from a gene of interest (red nodes). ',
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+ 'Components and communities are densely linked group of genes with the ',
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+ 'difference that the genes sharing common properties are maintained ',
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+ 'within the graph (green nodes).')
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+
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+knitr::include_graphics('figures/fig1.png')
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+```
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The component category extracts strongly connected group of genes
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along with the corresponding parameters are shown in Table 6.
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-```{r, eval=TRUE, echo=FALSE, results = 'asis'}
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-
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-data <- c( '**Topological**', '', "",
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-'Degree', 'Number adjacent interactions of the gene', "'degree'",
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-'Betweenness', 'Number of shortest paths from all vertices to all',
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-"'betweenness'",
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-'', 'others that pass through that node', "",
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-'Closeness', 'Inverse of farness, which is the sum of distances',
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-"'closeness'",
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-'', 'to all other nodes', '',
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-'Hub score', 'Kleinbergs hub centrality score', "'hub_score'",
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-'Eccentricity', 'Shortest path distance from the farthest', "'eccentricity'",
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-'', 'node in the graph', '',
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-'Page rank', 'Google Page Rank', "'page_rank'",
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-'Start Nodes', 'Nodes without any incoming links', "'start_nodes'",
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-'**Functional**', '', "",
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-'DEG', 'Genes highly differentially expressed', "'deg'",
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-'', 'according to the experimental data', '',
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-'Pathways', 'Genes acting as bridges among KEGG pathways', "'KEGG'",
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-'Biological Process', 'Genes acting as bridges among', "'GO_bp'",
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-'', 'Gene Ontology Biological Process terms', '',
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-'Cellular Component', 'Genes acting as bridges among', "'GO_cc'",
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-'', 'Gene Ontology Cellular Component terms', '',
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-'Molecular Function', 'Genes acting as bridges among', "'GO_mf'",
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-'', 'Gene Ontology Molecular Function terms', '',
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-'Disease', 'Genes acting as bridges for OMIM targets', "'Disease_OMIM'",
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-'Disease', 'Genes acting as bridges for GAD targets', "'Disease_GAD'",
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-'Drug', 'Genes acting as bridges for DrugBank targets', "'Drug_DrugBank'",
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-'microRNA', 'Genes acting as bridges for microRNA targets', "'miRNA'",
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-'Transcription Factors', 'Genes acting as bridges for TF targets', "'TF'"
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-)
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-data <- matrix(data, nrow=26, ncol=3, byrow=TRUE)
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-
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-rownames(data) <- rep('', nrow(data))
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-colnames(data) <- c('Type', 'Description', 'R parameter')
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-
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-kable( data,
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- caption = 'Gene of interest (GOI) types' )
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-```
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+Type Description R command
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+--------------------- ---------------------------------------------------- ----------------
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+**Topological**
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+Degree Number of adjacent interactions of the gene 'degree'
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+Betweenness Number of shortest paths from all vertices to all 'betweenness'
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+ others that pass through that node
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+Closeness Inverse of farness, which is the sum of distances 'closeness'
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+ to all other nodes
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+Hub score Kleinbergs hub centrality score 'hub_score'
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+Eccentricity Shortest path distance from the farthest 'eccentricity'
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+ node in the graph
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+Page rank Google Page Rank 'page_rank'
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+Start Nodes Nodes without any incoming links 'start_nodes'
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+**Functional**
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+DEG Genes highly differentially expressed 'deg'
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+ according to the experimental data
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+Pathways Genes acting as bridges among KEGG pathways 'KEGG'
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+Biological Process Genes acting as bridges among 'GO_bp'
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+ Gene Ontology Biological Process terms
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+Cellular Component Genes acting as bridges among 'GO_cc'
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+ Gene Ontology Cellular Component terms
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+Molecular Function Genes acting as bridges among 'GO_mf'
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+ Gene Ontology Molecular Function terms
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+Disease Genes acting as bridges for OMIM targets 'Disease_OMIM'
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+Disease Genes acting as bridges for GAD targets 'Disease_GAD'
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+Drug Genes acting as bridges for DrugBank targets 'Drug_DrugBank'
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+microRNA Genes acting as bridges for microRNA targets 'miRNA'
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+Transcription Factors Genes acting as bridges for TF targets 'TF'
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+--------------------- ---------------------------------------------------- ----------------
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+Table: Gene of interest (GOI) types
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+
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+
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### 5.3. All subpathway options
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...
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@@ -346,224 +329,171 @@ sixteen and the community-based types are six based on igraph package.
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DEsubs therefore supports 124 subpathway types as described in Tables 7-11.
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-
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-data <- c(
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-'**Topological**', '',
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-'Forward and backward streams starting from',
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-"'fwd.stream.topological.degree'",
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-'genes/nodes with crucial topological roles',
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-"'fwd.stream.topological.betweenness'",
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-'within the network', "'fwd.stream.topological.closeness'",
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-'', "'fwd.stream.topological.hub_score'",
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-'', "'fwd.stream.topological.eccentricity'",
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-'', "'fwd.stream.topological.page_rank'",
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-'', "'fwd.stream.topological.start_nodes'",
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-'', "'bwd.stream.topological.degree'",
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-'', "'bwd.stream.topological.betweenness'",
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-'', "'bwd.stream.topological.closeness'",
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-'', "'bwd.stream.topological.hub_score'",
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-'', "'bwd.stream.topological.eccentricity'",
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-'', "'bwd.stream.topological.page_rank'",
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-'', "'bwd.stream.topological.start_nodes'",
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-'**Functional**', '',
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-'Forward and backward streams starting from', "'fwd.stream.functional.GO_bp'",
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-'genes/nodes with crucial functional role', "'fwd.stream.functional.GO_cc'",
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-'within the network', "'fwd.stream.functional.GO_mf'",
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373
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-'', "'fwd.stream.functional.Disease_OMIM'",
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|
374
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-'', "'fwd.stream.functional.Disease_GAD'",
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-'', "'fwd.stream.functional.Drug_DrugBank'",
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-'', "'fwd.stream.functional.miRNA'",
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-'', "'fwd.stream.functional.TF'",
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-'', "'fwd.stream.functional.KEGG_pathways'",
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-'', "'fwd.stream.functional.DEG'",
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-'', "'bwd.stream.functional.GO_bp'",
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-'', "'bwd.stream.functional.GOC_cc",
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382
|
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-'', "'bwd.stream.functional.GO_mf'",
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|
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-'', "'bwd.stream.functional.Disease_OMIM'",
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384
|
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-'', "'bwd.stream.functional.Disease_GAD'",
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|
385
|
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-'', "'bwd.stream.functional.Drug_DrugBank'",
|
|
386
|
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-'', "'bwd.stream.functional.miRNA'",
|
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387
|
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-'', "'bwd.stream.functional.TF'",
|
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388
|
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-'', "'bwd.stream.functional. KEGG_pathways'",
|
|
389
|
|
-'', "'bwd.stream.functional.DEG'")
|
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390
|
|
-data <- matrix(data, nrow=36, ncol=2, byrow=TRUE)
|
|
391
|
|
-
|
|
392
|
|
-rownames(data) <- rep('', nrow(data))
|
|
393
|
|
-colnames(data) <- c('Desciption', 'R parameter')
|
|
394
|
|
-
|
|
395
|
|
-kable( data,
|
|
396
|
|
- caption = 'Subpathway Options - STREAM' )
|
|
397
|
|
-```
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398
|
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-
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399
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-
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400
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-
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401
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-```{r, eval=TRUE, echo=FALSE, results = 'asis'}
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-
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403
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-
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404
|
|
-data <- c(
|
|
405
|
|
-'**Topological**', '',
|
|
406
|
|
-'Forward and backward streams starting from ',
|
|
407
|
|
- "'fwd.neighbourhood.topological.degree'",
|
|
408
|
|
-'genes/nodes with crucial topological role',
|
|
409
|
|
- "'fwd.neighbourhood.topological.betweenness'",
|
|
410
|
|
-' within the network', "'fwd.neighbourhood.topological.closeness'",
|
|
411
|
|
-'', "'fwd.neighbourhood.topological.hub_score'",
|
|
412
|
|
-'', "'fwd.neighbourhood.topological.eccentricity'",
|
|
413
|
|
-'', "'fwd.neighbourhood.topological.page_rank'",
|
|
414
|
|
-'', "'fwd.neighbourhood.topological.start_nodes'",
|
|
415
|
|
-'', "'bwd.neighbourhood.topological.degree'",
|
|
416
|
|
-'', "'bwd.neighbourhood.topological.betweenness'",
|
|
417
|
|
-'', "'bwd.neighbourhood.topological.closeness'",
|
|
418
|
|
-'', "'bwd.neighbourhood.topological.hub_score'",
|
|
419
|
|
-'', "'bwd.neighbourhood.topological.eccentricity'",
|
|
420
|
|
-'', "'bwd.neighbourhood.topological.page_rank'",
|
|
421
|
|
-'', "'bwd.neighbourhood.topological.start_nodes'",
|
|
422
|
|
-'**Functional**', '',
|
|
423
|
|
-'Forward and backward streams starting from ',
|
|
424
|
|
- "'fwd.neighbourhood.functional.GO_bp'",
|
|
425
|
|
-'genes/nodes with crucial functional role ',
|
|
426
|
|
- "'fwd.neighbourhood.functional.GO_cc'",
|
|
427
|
|
-'within the network',
|
|
428
|
|
- "'fwd.neighbourhood.functional.GO_mf'",
|
|
429
|
|
-'',
|
|
430
|
|
- "'fwd.neighbourhood.functional.Disease_OMIM'",
|
|
431
|
|
-'', "'fwd.neighbourhood.functional.Disease_GAD'",
|
|
432
|
|
-'', "'fwd.neighbourhood.functional.Drug_DrugBank'",
|
|
433
|
|
-'', "'fwd.neighbourhood.functional.miRNA'",
|
|
434
|
|
-'', "'fwd.neighbourhood.functional.TF'",
|
|
435
|
|
-'', "'fwd.neighbourhood.functional.KEGG_pathways'",
|
|
436
|
|
-'', "'fwd.neighbourhood.functional.DEG'",
|
|
437
|
|
-'', "'bwd.neighbourhood.functional.GO_bp'",
|
|
438
|
|
-'', "'bwd.neighbourhood.functional.GOC_cc",
|
|
439
|
|
-'', "'bwd.neighbourhood.functional.GO_mf'",
|
|
440
|
|
-'', "'bwd.neighbourhood.functional.Disease_OMIM'",
|
|
441
|
|
-'', "'bwd.neighbourhood.functional.Disease_GAD'",
|
|
442
|
|
-'', "'bwd.neighbourhood.functional.Drug_DrugBank'",
|
|
443
|
|
-'', "'bwd.neighbourhood.functional.miRNA'",
|
|
444
|
|
-'', "'bwd.neighbourhood.functional.TF'",
|
|
445
|
|
-'', "'bwd.neighbourhood.functional. KEGG_pathways'",
|
|
446
|
|
-'', "'bwd.neighbourhood.functional.DEG'")
|
|
447
|
|
-data <- matrix(data, nrow=36, ncol=2, byrow=TRUE)
|
|
448
|
|
-
|
|
449
|
|
-rownames(data) <- rep('', nrow(data))
|
|
450
|
|
-colnames(data) <- c('Desciption', 'R parameter')
|
|
451
|
|
-
|
|
452
|
|
-kable( data,
|
|
453
|
|
- caption = 'Subpathway Options - NEIGHBOURHOOD' )
|
|
454
|
|
-```
|
|
455
|
|
-
|
|
456
|
|
-
|
|
457
|
|
-
|
|
|
332
|
+Description R parameter
|
|
|
333
|
+----------------------------------------------- -----------------------------------------------
|
|
|
334
|
+**Topological**
|
|
|
335
|
+Forward and backward streams starting from 'fwd.stream.topological.degree'
|
|
|
336
|
+genes/nodes with crucial topological roles 'fwd.stream.topological.betweenness'
|
|
|
337
|
+within the network 'fwd.stream.topological.closeness'
|
|
|
338
|
+ 'fwd.stream.topological.hub_score'
|
|
|
339
|
+ 'fwd.stream.topological.eccentricity'
|
|
|
340
|
+ 'fwd.stream.topological.page_rank'
|
|
|
341
|
+ 'fwd.stream.topological.start_nodes'
|
|
|
342
|
+ 'bwd.stream.topological.degree'
|
|
|
343
|
+ 'bwd.stream.topological.betweenness'
|
|
|
344
|
+ 'bwd.stream.topological.closeness'
|
|
|
345
|
+ 'bwd.stream.topological.hub_score'
|
|
|
346
|
+ 'bwd.stream.topological.eccentricity'
|
|
|
347
|
+ 'bwd.stream.topological.page_rank'
|
|
|
348
|
+ 'bwd.stream.topological.start_nodes'
|
|
|
349
|
+**Functional**
|
|
|
350
|
+Forward and backward streams starting from 'fwd.stream.functional.GO_bp'
|
|
|
351
|
+genes/nodes with crucial functional roles 'fwd.stream.functional.GO_cc'
|
|
|
352
|
+within the network 'fwd.stream.functional.GO_mf'
|
|
|
353
|
+ 'fwd.stream.functional.Disease_OMIM'
|
|
|
354
|
+ 'fwd.stream.functional.Disease_GAD'
|
|
|
355
|
+ 'fwd.stream.functional.Drug_DrugBank'
|
|
|
356
|
+ 'fwd.stream.functional.miRNA'
|
|
|
357
|
+ 'fwd.stream.functional.TF'
|
|
|
358
|
+ 'fwd.stream.functional.KEGG'
|
|
|
359
|
+ 'fwd.stream.functional.DEG'
|
|
|
360
|
+ 'bwd.stream.functional.GO_bp'
|
|
|
361
|
+ 'bwd.stream.functional.GO_cc'
|
|
|
362
|
+ 'bwd.stream.functional.GO_mf'
|
|
|
363
|
+ 'bwd.stream.functional.Disease_OMIM'
|
|
|
364
|
+ 'bwd.stream.functional.Disease_GAD'
|
|
|
365
|
+ 'bwd.stream.functional.Drug_DrugBank'
|
|
|
366
|
+ 'bwd.stream.functional.miRNA'
|
|
|
367
|
+ 'bwd.stream.functional.TF'
|
|
|
368
|
+ 'bwd.stream.functional.KEGG'
|
|
|
369
|
+ 'bwd.stream.functional.DEG'
|
|
|
370
|
+----------------------------------------------- -----------------------------------------------
|
|
|
371
|
+Table: Subpathway Options - STREAM
|
|
|
372
|
+
|
|
|
373
|
+
|
|
|
374
|
+
|
|
|
375
|
+
|
|
|
376
|
+Description R parameter
|
|
|
377
|
+----------------------------------------------- -----------------------------------------------
|
|
|
378
|
+**Topological**
|
|
|
379
|
+Forward and backward neighbourhoods starting 'fwd.neighbourhood.topological.degree'
|
|
|
380
|
+from genes/nodes with crucial topological 'fwd.neighbourhood.topological.betweenness'
|
|
|
381
|
+roles within the network 'fwd.neighbourhood.topological.closeness'
|
|
|
382
|
+ 'fwd.neighbourhood.topological.hub_score'
|
|
|
383
|
+ 'fwd.neighbourhood.topological.eccentricity'
|
|
|
384
|
+ 'fwd.neighbourhood.topological.page_rank'
|
|
|
385
|
+ 'fwd.neighbourhood.topological.start_nodes'
|
|
|
386
|
+ 'bwd.neighbourhood.topological.degree'
|
|
|
387
|
+ 'bwd.neighbourhood.topological.betweenness'
|
|
|
388
|
+ 'bwd.neighbourhood.topological.closeness'
|
|
|
389
|
+ 'bwd.neighbourhood.topological.hub_score'
|
|
|
390
|
+ 'bwd.neighbourhood.topological.eccentricity'
|
|
|
391
|
+ 'bwd.neighbourhood.topological.page_rank'
|
|
|
392
|
+ 'bwd.neighbourhood.topological.start_nodes'
|
|
|
393
|
+**Functional**
|
|
|
394
|
+Forward and backward neighbourhoods starting 'fwd.neighbourhood.functional.GO_bp'
|
|
|
395
|
+from genes/nodes with crucial topological 'fwd.neighbourhood.functional.GO_cc'
|
|
|
396
|
+roles within the network 'fwd.neighbourhood.functional.GO_mf'
|
|
|
397
|
+ 'fwd.neighbourhood.functional.Disease_OMIM'
|
|
|
398
|
+ 'fwd.neighbourhood.functional.Disease_GAD'
|
|
|
399
|
+ 'fwd.neighbourhood.functional.Drug_DrugBank'
|
|
|
400
|
+ 'fwd.neighbourhood.functional.miRNA'
|
|
|
401
|
+ 'fwd.neighbourhood.functional.TF'
|
|
|
402
|
+ 'fwd.neighbourhood.functional.KEGG'
|
|
|
403
|
+ 'fwd.neighbourhood.functional.DEG'
|
|
|
404
|
+ 'bwd.neighbourhood.functional.GO_bp'
|
|
|
405
|
+ 'bwd.neighbourhood.functional.GO_cc'
|
|
|
406
|
+ 'bwd.neighbourhood.functional.GO_mf'
|
|
|
407
|
+ 'bwd.neighbourhood.functional.Disease_OMIM'
|
|
|
408
|
+ 'bwd.neighbourhood.functional.Disease_GAD'
|
|
|
409
|
+ 'bwd.neighbourhood.functional.Drug_DrugBank'
|
|
|
410
|
+ 'bwd.neighbourhood.functional.miRNA'
|
|
|
411
|
+ 'bwd.neighbourhood.functional.TF'
|
|
|
412
|
+ 'bwd.neighbourhood.functional.KEGG'
|
|
|
413
|
+ 'bwd.neighbourhood.functional.DEG'
|
|
|
414
|
+----------------------------------------------- -----------------------------------------------
|
|
|
415
|
+Table: Subpathway Options - NEIGHBOURHOOD
|
|
|
416
|
+
|
|
|
417
|
+
|
|
|
418
|
+
|
|
|
419
|
+
|
|
|
420
|
+Description R parameter
|
|
|
421
|
+----------------------------------------------- -----------------------------------------------
|
|
|
422
|
+**Topological**
|
|
|
423
|
+Forward and backward cascades starting 'fwd.cascade.topological.degree'
|
|
|
424
|
+from genes/nodes with crucial topological 'fwd.cascade.topological.betweenness'
|
|
|
425
|
+roles within the network 'fwd.cascade.topological.closeness'
|
|
|
426
|
+ 'fwd.cascade.topological.hub_score'
|
|
|
427
|
+ 'fwd.cascade.topological.eccentricity'
|
|
|
428
|
+ 'fwd.cascade.topological.page_rank'
|
|
|
429
|
+ 'fwd.cascade.topological.start_nodes'
|
|
|
430
|
+ 'bwd.cascade.topological.degree'
|
|
|
431
|
+ 'bwd.cascade.topological.betweenness'
|
|
|
432
|
+ 'bwd.cascade.topological.closeness'
|
|
|
433
|
+ 'bwd.cascade.topological.hub_score'
|
|
|
434
|
+ 'bwd.cascade.topological.eccentricity'
|
|
|
435
|
+ 'bwd.cascade.topological.page_rank'
|
|
|
436
|
+ 'bwd.cascade.topological.start_nodes'
|
|
|
437
|
+**Functional**
|
|
|
438
|
+Forward and backward cascades starting 'fwd.cascade.functional.GO_bp'
|
|
|
439
|
+from genes/nodes with crucial topological 'fwd.cascade.functional.GO_cc'
|
|
|
440
|
+roles within the network 'fwd.cascade.functional.GO_mf'
|
|
|
441
|
+ 'fwd.cascade.functional.Disease_OMIM'
|
|
|
442
|
+ 'fwd.cascade.functional.Disease_GAD'
|
|
|
443
|
+ 'fwd.cascade.functional.Drug_DrugBank'
|
|
|
444
|
+ 'fwd.cascade.functional.miRNA'
|
|
|
445
|
+ 'fwd.cascade.functional.TF'
|
|
|
446
|
+ 'fwd.cascade.functional.KEGG'
|
|
|
447
|
+ 'fwd.cascade.functional.DEG'
|
|
|
448
|
+ 'bwd.cascade.functional.GO_bp'
|
|
|
449
|
+ 'bwd.cascade.functional.GO_cc'
|
|
|
450
|
+ 'bwd.cascade.functional.GO_mf'
|
|
|
451
|
+ 'bwd.cascade.functional.Disease_OMIM'
|
|
|
452
|
+ 'bwd.cascade.functional.Disease_GAD'
|
|
|
453
|
+ 'bwd.cascade.functional.Drug_DrugBank'
|
|
|
454
|
+ 'bwd.cascade.functional.miRNA'
|
|
|
455
|
+ 'bwd.cascade.functional.TF'
|
|
|
456
|
+ 'bwd.cascade.functional.KEGG'
|
|
|
457
|
+ 'bwd.cascade.functional.DEG'
|
|
|
458
|
+----------------------------------------------- -----------------------------------------------
|
|
|
459
|
+Table: Subpathway Options - CASCADE
|
|
|
460
|
+
|
|
|
461
|
+
|
|
|
462
|
+
|
|
|
463
|
+Type Description R parameter
|
|
|
464
|
+------------------ ------------------------------------- --------------------------------------
|
|
|
465
|
+Random Walk Community structures that minimize 'community.infomap'
|
|
|
466
|
+ the expected description length of
|
|
|
467
|
+ a random walker trajectory
|
|
|
468
|
+Modular Community structures via a modularity 'community.louvain'
|
|
|
469
|
+ measure and a hierarchical approach
|
|
|
470
|
+Walktraps Densely connected subgraphs via 'community.walktrap'
|
|
|
471
|
+ random walks
|
|
|
472
|
+Leading eigen Densely connected subgraphs based 'community.leading_eigen'
|
|
|
473
|
+ on the leading non-negative eigen-
|
|
|
474
|
+ vector of the modularity matrix
|
|
|
475
|
+Betweeneess Community structures detection 'community.edge_betweenness'
|
|
|
476
|
+ via edge betweenness
|
|
|
477
|
+Greedy Community structures via greedy 'community.fast_greedy'
|
|
|
478
|
+ optimization of modularity
|
|
|
479
|
+------------------ ------------------------------------- --------------------------------------
|
|
|
480
|
+Table: Subpathway Options - COMMUNITY
|
|
|
481
|
+
|
|
|
482
|
+
|
|
|
483
|
+
|
|
|
484
|
+Type Description R parameter
|
|
|
485
|
+------------------ ------------------------------------- --------------------------------------
|
|
|
486
|
+Cliques A subgraph where every two distinct 'component.3-cliques'
|
|
|
487
|
+ vertices in the clique are adjacent ...
|
|
|
488
|
+ 'component.9-cliques'
|
|
|
489
|
+K-core A maximal subgraph in which each 'component.3-coreness'
|
|
|
490
|
+ vertex has at least degree k ...
|
|
|
491
|
+ 'component.9-coreness'
|
|
|
492
|
+Max cliques Largest of maximal cliques 'component.max_cliques'
|
|
|
493
|
+Components All single components 'component.decompose'
|
|
|
494
|
+------------------ ------------------------------------- --------------------------------------
|
|
|
495
|
+Table: Subpathway Options - COMPONENT
|
|
458
|
496
|
|
|
459
|
|
-```{r, eval=TRUE, echo=FALSE, results = 'asis'}
|
|
460
|
|
-
|
|
461
|
|
-data <- c(
|
|
462
|
|
-'**Topological**', '',
|
|
463
|
|
-'Forward and backward streams starting from',
|
|
464
|
|
- "'fwd.cascade.topological.degree'",
|
|
465
|
|
-'genes/nodes with crucial topological role',
|
|
466
|
|
- "'fwd.cascade.topological.betweenness'",
|
|
467
|
|
-'within the network',
|
|
468
|
|
- "'fwd.cascade.topological.closeness'",
|
|
469
|
|
-'', "'fwd.cascade.topological.hub_score'",
|
|
470
|
|
-'', "'fwd.cascade.topological.eccentricity'",
|
|
471
|
|
-'', "'fwd.cascade.topological.page_rank'",
|
|
472
|
|
-'', "'fwd.cascade.topological.start_nodes'",
|
|
473
|
|
-'', "'bwd.cascade.topological.degree'",
|
|
474
|
|
-'', "'bwd.cascade.topological.betweenness'",
|
|
475
|
|
-'', "'bwd.cascade.topological.closeness'",
|
|
476
|
|
-'', "'bwd.cascade.topological.hub_score'",
|
|
477
|
|
-'', "'bwd.cascade.topological.eccentricity'",
|
|
478
|
|
-'', "'bwd.cascade.topological.page_rank'",
|
|
479
|
|
-'', "'bwd.cascade.topological.start_nodes'",
|
|
480
|
|
-'**Functional**', '',
|
|
481
|
|
-'Forward and backward streams starting from',
|
|
482
|
|
- "'fwd.cascade.functional.GO_bp'",
|
|
483
|
|
-'genes/nodes with crucial functional role',
|
|
484
|
|
- "'fwd.cascade.functional.GO_cc'",
|
|
485
|
|
-'within the network',
|
|
486
|
|
- "'fwd.cascade.functional.GO_mf'",
|
|
487
|
|
-'',
|
|
488
|
|
- "'fwd.cascade.functional.Disease_OMIM'",
|
|
489
|
|
-'', "'fwd.cascade.functional.Disease_GAD'",
|
|
490
|
|
-'', "'fwd.cascade.functional.Drug_DrugBank'",
|
|
491
|
|
-'', "'fwd.cascade.functional.miRNA'",
|
|
492
|
|
-'', "'fwd.cascade.functional.TF'",
|
|
493
|
|
-'', "'fwd.cascade.functional.KEGG'",
|
|
494
|
|
-'', "'fwd.cascade.functional.DEG'",
|
|
495
|
|
-'', "'bwd.cascade.functional.GO_bp'",
|
|
496
|
|
-'', "'bwd.cascade.functional.GOC_cc",
|
|
497
|
|
-'', "'bwd.cascade.functional.GO_mf'",
|
|
498
|
|
-'', "'bwd.cascade.functional.Disease_OMIM'",
|
|
499
|
|
-'', "'bwd.cascade.functional.Disease_GAD'",
|
|
500
|
|
-'', "'bwd.cascade.functional.Drug_DrugBank'",
|
|
501
|
|
-'', "'bwd.cascade.functional.miRNA'",
|
|
502
|
|
-'', "'bwd.cascade.functional.TF'",
|
|
503
|
|
-'', "'bwd.cascade.functional.KEGG'",
|
|
504
|
|
-'', "'bwd.cascade.functional.DEG'")
|
|
505
|
|
-data <- matrix(data, nrow=36, ncol=2, byrow=TRUE)
|
|
506
|
|
-
|
|
507
|
|
-rownames(data) <- rep('', nrow(data))
|
|
508
|
|
-colnames(data) <- c('Desciption', 'R parameter')
|
|
509
|
|
-
|
|
510
|
|
-kable( data,
|
|
511
|
|
- caption = 'Subpathway Options - CASCADE' )
|
|
512
|
|
-```
|
|
513
|
|
-
|
|
514
|
|
-
|
|
515
|
|
-
|
|
516
|
|
-
|
|
517
|
|
-
|
|
518
|
|
-```{r, eval=TRUE, echo=FALSE, results = 'asis'}
|
|
519
|
|
-
|
|
520
|
|
-data <- c(
|
|
521
|
|
-'Random Walk', 'Community structures that minimize ', "'community.infomap'",
|
|
522
|
|
-'', 'the expected description length of', "",
|
|
523
|
|
-'', 'a random walker trajectory', "",
|
|
524
|
|
-'Modular', 'Community structures via a modularity ', "'community.louvain'",
|
|
525
|
|
-'', 'measure and a hierarchical approach', "",
|
|
526
|
|
-'Walktraps', 'Densely connected subgraphs via', "'community.walktrap'",
|
|
527
|
|
-'', 'random walks', '',
|
|
528
|
|
-'Leading eigen', 'Densely connected subgraphs based ',
|
|
529
|
|
-"'community.leading_eigen'",
|
|
530
|
|
-'', 'on the leading non-negative eigen-', '',
|
|
531
|
|
-'', 'vector of the modularity matrix', '',
|
|
532
|
|
-'Betweeneess','Community structures detection',"'community.edge_betweenness'",
|
|
533
|
|
-'', 'via edge betweenness', '',
|
|
534
|
|
-'Greedy', 'Community structures via greedy ', "'community.fast_greedy'",
|
|
535
|
|
-'', 'optimization of modularity', '')
|
|
536
|
|
-
|
|
537
|
|
-data <- matrix(data, nrow=14, ncol=3, byrow=TRUE)
|
|
538
|
|
-
|
|
539
|
|
-rownames(data) <- rep('', nrow(data))
|
|
540
|
|
-colnames(data) <- c('Type', 'Desciption', 'R parameter')
|
|
541
|
|
-
|
|
542
|
|
-kable( data,
|
|
543
|
|
- caption = 'Subpathway Options - COMMUNITY' )
|
|
544
|
|
-```
|
|
545
|
|
-
|
|
546
|
|
-
|
|
547
|
|
-
|
|
548
|
|
-```{r, eval=TRUE, echo=FALSE, results = 'asis'}
|
|
549
|
|
-
|
|
550
|
|
-data <- c('Cliques', 'A subgraph where every two distinct',
|
|
551
|
|
-"'component.3-cliques', ",
|
|
552
|
|
-'', 'vertices in the clique are adjacent', " .... ",
|
|
553
|
|
-'', '', "'component.9-cliques', ",
|
|
554
|
|
-'K-core', 'A maximal subgraph in which each', "'component.3-coreness'",
|
|
555
|
|
-'', 'vertex has at least degree k', " .... ",
|
|
556
|
|
-'', '', "'component.9-coreness'",
|
|
557
|
|
-'Max cliques', 'Largest of maximal cliques', "'component.max_cliques'",
|
|
558
|
|
-'Components', 'All single components', "'component.decompose'")
|
|
559
|
|
-data <- matrix(data, nrow=8, ncol=3, byrow=TRUE)
|
|
560
|
|
-
|
|
561
|
|
-rownames(data) <- rep('', nrow(data))
|
|
562
|
|
-colnames(data) <- c('Type', 'Desciption', 'R parameter')
|
|
563
|
|
-
|
|
564
|
|
-kable( data,
|
|
565
|
|
- caption = 'Subpathway Options - COMPONENT' )
|
|
566
|
|
-```
|
|
567
|
497
|
|
|
568
|
498
|
|
|
569
|
499
|
An example follows where *community.walktrap* is selected as the
|
|
...
|
...
|
@@ -585,15 +515,21 @@ DEsubs.run <- DEsubs(
|
|
585
|
515
|
|
|
586
|
516
|
\newpage
|
|
587
|
517
|
|
|
588
|
|
-{height=750px}
|
|
595
|
518
|
|
|
596
|
519
|
|
|
|
520
|
+```{r eval=TRUE, echo=FALSE, out.height='575px', fig.align='center', fig.cap=cap}
|
|
|
521
|
+
|
|
|
522
|
+cap <- paste0(
|
|
|
523
|
+ 'Subpathway extraction options consist of five main categories. ',
|
|
|
524
|
+ 'The three of them (cascade, neighborhood, stream) are sub-categorized ',
|
|
|
525
|
+ 'according to features (topological or functional) and the direction of ',
|
|
|
526
|
+ 'propagation (forward or backward) of the gene of interest where each ',
|
|
|
527
|
+ 'subpathway is starting. The other two (component, community) are ',
|
|
|
528
|
+ 'sub-categorized according to various topological properties.')
|
|
|
529
|
+
|
|
|
530
|
+knitr::include_graphics('figures/fig2.png')
|
|
|
531
|
+```
|
|
|
532
|
+
|
|
597
|
533
|
|
|
598
|
534
|
## 6. Subpathway enrichment analysis
|
|
599
|
535
|
|
|
...
|
...
|
@@ -639,20 +575,15 @@ Transcription Factor Gene targetsof transcription [@chen2013enrichr]
|
|
639
|
575
|
Table: List of external databases
|
|
640
|
576
|
|
|
641
|
577
|
|
|
642
|
|
-```{r, eval=TRUE, echo=FALSE, results = 'asis'}
|
|
643
|
|
-
|
|
644
|
|
-data <- c( 'ACAD9', 'ACAD8', 'SH3GLB1', 'ESCO2', 'ESCO1', 'ADH1C', '"0"',
|
|
645
|
|
- 'ADH1C', 'ADH1B', 'ADHFE1', 'ADH1A', 'ADH6', 'ADH7', 'ADH4',
|
|
646
|
|
- '...', '...', '...', '...', '...', '...', '...',
|
|
647
|
|
- 'PTPN1', 'RHOA', 'ACTN4', 'ACTN3', 'ACTN2', '"0"', '"0"')
|
|
648
|
|
-data <- matrix(data, nrow=4, ncol=7, byrow=TRUE)
|
|
|
578
|
+Term Target 1 Target 2 Target 3 Target 4 Target 5 Target 6 Target 7
|
|
|
579
|
+--------- --------- --------- --------- --------- --------- --------- ---------
|
|
|
580
|
+Term 1 ACAD9 ACAD8 SH3GLB1 ESCO2 ESCO1 ADH1C '0'
|
|
|
581
|
+Term 2 ADH1C ADH1B ADHFE1 ADH1A ADH6 ADH7 ADH4
|
|
|
582
|
+... ... ... ... ... ... ... ...
|
|
|
583
|
+Term N PTPN1 RHOA ACTN4 ACTN3 ACTN2 '0' '0'
|
|
|
584
|
+--------- --------- --------- --------- --------- --------- --------- ---------
|
|
|
585
|
+Table: Example of custom gene set
|
|
649
|
586
|
|
|
650
|
|
-rownames(data) <- c(paste0('Term ', 1:2), '...', 'Term N')
|
|
651
|
|
-colnames(data) <- paste0('Target ', 1:7)
|
|
652
|
|
-
|
|
653
|
|
-kable( data,
|
|
654
|
|
- caption = 'Example of custom gene set' )
|
|
655
|
|
-```
|
|
656
|
587
|
|
|
657
|
588
|
|
|
658
|
589
|
|
|
...
|
...
|
@@ -664,26 +595,34 @@ kable( data,
|
|
664
|
595
|
## 7. Visualization
|
|
665
|
596
|
|
|
666
|
597
|
DEsubs visualizes its results at a gene, subpathway and organism level through
|
|
667
|
|
-various schemes such as bar plots, heat maps, directed weighted graphs, z
|
|
668
|
|
-circular diagrams and dot plots. Indicative examples are illustrated in
|
|
669
|
|
-figures 2-8 based on DEsubs executions using the human pathway network and
|
|
670
|
|
-a synthetic dataset. Bar plots show the genes with the best Q-value from the
|
|
671
|
|
-user-selected DE analysis tool (the user defines the desired gene number).
|
|
672
|
|
-The figures are exported in the directory *Output* within the user specified
|
|
673
|
|
-location. Heat maps show the genes with the highest values either in our
|
|
674
|
|
-topological or functional measures (see Table 6).
|
|
675
|
|
-
|
|
676
|
|
-![Bar plots show the genes with the best Q-value from the user-selected
|
|
677
|
|
-DE analysis tool (the user defines the desired gene number). Heat maps show
|
|
678
|
|
-the genes with the highest values either in our topological or functional
|
|
679
|
|
-measures (see Table 6). Each extracted subpathway is illustrated though a
|
|
680
|
|
-directed graph by imprinting the degree of DE and correlation among the
|
|
681
|
|
-respective gene members. Subpathway enrichment in association with biological
|
|
682
|
|
-and pharmacological features (such as pathway terms, gene ontologies,
|
|
683
|
|
-regulators, diseases and drug targets) is depicted through circular diagrams
|
|
684
|
|
-[@gu2014circlize].
|
|
685
|
|
-The total picture of the enriched subpathways is performed with dot plots.
|
|
686
|
|
-](figures/fig3.png "Visualization overview."){height=500px}
|
|
|
598
|
+various schemes such as bar plots, heat maps, directed weighted graphs,
|
|
|
599
|
+circular diagrams [@gu2014circlize] and dot plots. Indicative examples are
|
|
|
600
|
+illustrated in figures 2-8 based on DEsubs executions using the human pathway
|
|
|
601
|
+network and a synthetic dataset. Bar plots show the genes with the best Q-value
|
|
|
602
|
+from the user-selected DE analysis tool (the user defines the desired gene
|
|
|
603
|
+number). The figures are exported in the directory *Output* within the user
|
|
|
604
|
+specified location. Heat maps show the genes with the highest values either
|
|
|
605
|
+in our topological or functional measures (see Table 6).
|
|
|
606
|
+
|
|
|
607
|
+
|
|
|
608
|
+```{r eval=TRUE, echo=FALSE, out.height='385px', fig.align='center', fig.cap=cap, fig.pos='h', out.extra=''}
|
|
|
609
|
+
|
|
|
610
|
+cap <- paste0(
|
|
|
611
|
+ 'Bar plots show the genes with the best Q-value from the user-selected ',
|
|
|
612
|
+ 'DE analysis tool (the user defines the desired gene number). ',
|
|
|
613
|
+ 'Heat maps show the genes with the highest values either in our ',
|
|
|
614
|
+ 'topological or functional measures (see Table 6). ',
|
|
|
615
|
+ 'Each extracted subpathway is illustrated though a directed graph by ',
|
|
|
616
|
+ 'imprinting the degree of DE and correlation among the respective gene ',
|
|
|
617
|
+ 'members. Subpathway enrichment in association with biological and ',
|
|
|
618
|
+ 'pharmacological features (such as pathway terms, gene ontologies, ',
|
|
|
619
|
+ 'regulators, diseases and drug targets) is depicted through circular ',
|
|
|
620
|
+ 'diagrams. The total picture of the enriched subpathways is performed ',
|
|
|
621
|
+ 'with dot plots.')
|
|
|
622
|
+
|
|
|
623
|
+knitr::include_graphics('figures/fig3.png')
|
|
|
624
|
+```
|
|
|
625
|
+
|
|
687
|
626
|
|
|
688
|
627
|
\newpage
|
|
689
|
628
|
|
