@@ -1,5 +1,5 @@

 Package: DEsubs

-Version: 1.3.3

+Version: 1.3.4

 Date: 2017-07-23

 Title: DEsubs: an R package for flexible identification of

         differentially expressed subpathways using RNA-seq expression

@@ -1,3 +1,6 @@

+1.3.4:  - Fixing (persistent) inconsistencies between vignette output within

+			the package and the output in the landing page.

+

 1.3.3:  - Replaced kable tables with pure markdown syntax.

         - Placed external figure importing within chunks.

@@ -130,13 +130,13 @@ the package itself (see Table 3).

 Supported Labels              R command

+------------------            --------------------------------------------------

 Entrez                        'entrezgene'

 Ensemble                      'ensembl_gene_id', 'ensembl_transcript_id'

                               'ensembl_peptide_id'

 HGNC                          'hgnc_id', 'hgnc_symbol', 'hgnc_transcript_name'

 Refseq                        'refseq_mrna', 'refseq_peptide'

+------------------            -------------------------------------------------

 Table: Supported gene labels

@@ -285,35 +285,35 @@ significant DEGs of his own experiment. A short description for all GOI types

 along with the corresponding parameters are shown in Table 6. 

-Type                  Description                                           R command

+Type                   Description                                           R command

+---------------------- ----------------------------------------------------  -------------

 **Topological**

-Degree                Number of adjacent interactions of the gene           'degree'

-Betweenness           Number of shortest paths from all vertices to all     'betweenness'

-                      others that pass through that node

-Closeness             Inverse of farness, which is the sum of distances     'closeness'

-                      to all other nodes

-Hub score             Kleinbergs hub centrality score                       'hub_score'

-Eccentricity          Shortest path distance from the farthest              'eccentricity'

-                      node in the graph

-Page rank             Google Page Rank                                      'page_rank'

-Start Nodes           Nodes without any incoming links                      'start_nodes'

+Degree                 Number of adjacent interactions of the gene           'degree'

+Betweenness            Number of shortest paths from all vertices to all     'betweenness'

+                       others that pass through that node

+Closeness              Inverse of farness, which is the sum of distances     'closeness'

+                       to all other nodes

+Hub score              Kleinbergs hub centrality score                       'hub_score'

+Eccentricity           Shortest path distance from the farthest              'eccentricity'

+                       node in the graph

+Page rank              Google Page Rank                                      'page_rank'

+Start Nodes            Nodes without any incoming links                      'start_nodes'

 **Functional**

-DEG                   Genes highly differentially expressed                 'deg'

-                      according to the experimental data

-Pathways              Genes acting as bridges among KEGG pathways           'KEGG'

-Biological Process    Genes acting as bridges among                         'GO_bp'

-                      Gene Ontology Biological Process terms

-Cellular Component    Genes acting as bridges among                         'GO_cc'

-                      Gene Ontology Cellular Component terms

-Molecular Function    Genes acting as bridges among                         'GO_mf'

-                      Gene Ontology Molecular Function terms

-Disease               Genes acting as bridges for OMIM targets              'Disease_OMIM'

-Disease               Genes acting as bridges for GAD targets               'Disease_GAD'

-Drug                  Genes acting as bridges for DrugBank targets          'Drug_DrugBank'

-microRNA              Genes acting as bridges for microRNA targets          'miRNA'

-Transcription Factors Genes acting as bridges for TF targets                'TF'

+DEG                    Genes highly differentially expressed                 'deg'

+                       according to the experimental data

+Pathways               Genes acting as bridges among KEGG pathways           'KEGG'

+Biological Process     Genes acting as bridges among                         'GO_bp'

+                       Gene Ontology Biological Process terms

+Cellular Component     Genes acting as bridges among                         'GO_cc'

+                       Gene Ontology Cellular Component terms

+Molecular Function     Genes acting as bridges among                         'GO_mf'

+                       Gene Ontology Molecular Function terms

+Disease                Genes acting as bridges for OMIM targets              'Disease_OMIM'

+Disease                Genes acting as bridges for GAD targets               'Disease_GAD'

+Drug                   Genes acting as bridges for DrugBank targets          'Drug_DrugBank'

+microRNA               Genes acting as bridges for microRNA targets          'miRNA'

+Transcription Factors  Genes acting as bridges for TF targets                'TF'

+---------------------- ----------------------------------------------------  -------------

 Table: Gene of interest (GOI) types

@@ -455,43 +455,43 @@ roles within the network                        'fwd.cascade.functional.GO_mf'

                                                 'bwd.cascade.functional.TF'

                                                 'bwd.cascade.functional.KEGG'

                                                 'bwd.cascade.functional.DEG'

+----------------------------------------------- -----------------------------------------------

 Table: Subpathway Options - CASCADE

-Type               Description                            R parameter

-Random Walk         Community structures that minimize    'community.infomap'

-                    the expected description length of

-                    a random walker trajectory

-Modular             Community structures via a modularity 'community.louvain'

-                    measure and a hierarchical approach

-Walktraps           Densely connected subgraphs via       'community.walktrap'

-                    random walks

-Leading eigen       Densely connected subgraphs based     'community.leading_eigen'

-                    on the leading non-negative eigen-

-                    vector of the modularity matrix

-Betweeneess         Community structures detection        'community.edge_betweenness'

-                    via edge betweenness

-Greedy              Community structures via greedy       'community.fast_greedy'

-                    optimization of modularity

+Type          Description                                 R parameter

+------------- ------------------------------------------  -------------------------------------

+Random Walk    Community structures that minimize         'community.infomap'

+               the expected description length of

+               a random walker trajectory

+Modular        Community structures via a modularity      'community.louvain'

+               measure and a hierarchical approach

+Walktraps      Densely connected subgraphs via            'community.walktrap'

+               random walks

+Leading eigen  Densely connected subgraphs based          'community.leading_eigen'

+               on the leading non-negative eigen-

+               vector of the modularity matrix

+Betweeneess    Community structures detection             'community.edge_betweenness'

+               via edge betweenness

+Greedy         Community structures via greedy            'community.fast_greedy'

+               optimization of modularity

+------------- ------------------------------------------  -------------------------------------

 Table: Subpathway Options - COMMUNITY

-Type               Description                            R parameter

-Cliques            A subgraph where every two distinct    'component.3-cliques'

-                   vertices in the clique are adjacent    ...

+Type          Description                                 R parameter

+------------- ------------------------------------------  -------------------------------------- 

+Cliques       A subgraph where every two distinct         'component.3-cliques'

+              vertices in the clique are adjacent          ...

                                                           'component.9-cliques'

-K-core             A maximal subgraph in which each       'component.3-coreness'

-                   vertex has at least degree k           ...

+K-core        A maximal subgraph in which each            'component.3-coreness'

+              vertex has at least degree k                ...

                                                           'component.9-coreness'

-Max cliques       Largest of maximal cliques              'component.max_cliques'

-Components        All single components                   'component.decompose'

+Max cliques   Largest of maximal cliques                  'component.max_cliques'

+Components    All single components                       'component.decompose'

+------------- ------------------------------------------  -------------------------------------- 

 Table: Subpathway Options - COMPONENT

@@ -644,7 +644,7 @@ res <- geneVisualization(

             export='plot', verbose=FALSE)

 ```

-```{r, echo=FALSE, fig.width=6.2, fig.height=5.2, fig.cap=cap }

+```{r, echo=FALSE, fig.width=6.2, fig.height=5.2, fig.cap=cap, fig.pos='h', out.extra='' }

 cap <- 'Bars illustrate the genes with the highest Q-values.'

@@ -660,7 +660,7 @@ res <- geneVisualization(

 ```

-```{r, echo=FALSE, fig.width=7, fig.height=4, fig.cap=cap  }

+```{r, echo=FALSE, fig.width=7, fig.height=4, fig.align='center', fig.cap=cap  }

 cap <- 'Heat map represents the twelve genes with the highest values of 

 functional measures. The values are scaled and the red graduation indicates 

@@ -720,7 +720,7 @@ res <- subpathwayToGraph(

 ```

-```{r, echo=FALSE, fig.width=3.5, fig.height=3.5, fig.cap=cap }

+```{r, echo=FALSE, fig.width=3.5, fig.height=3.5, fig.align='center', fig.cap=cap, fig.pos='h', out.extra='' }

 library('DEsubs')

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

@@ -756,7 +756,7 @@ res <- subpathwayVisualization(

 ```

-```{r, echo=FALSE, fig.width=3.8, fig.height=3.8, fig.cap=cap }

+```{r, echo=FALSE, fig.width=3.8, fig.height=3.8, fig.align='center', fig.cap=cap }

 cap <- 'Circular Diagram shows the associations among genes including in a 

 subpathway and Gene Ontology terms where are enriched'

@@ -774,7 +774,7 @@ res <- subpathwayVisualization(

                     verbose=FALSE)

 ```

-```{r, echo=FALSE, fig.width=4.0, fig.height=4.0, fig.cap=cap }

+```{r, echo=FALSE, fig.width=4.0, fig.height=4.0, fig.align='center', fig.cap=cap }

 cap <- 'Circular Diagram shows the associations among genes included in a 

 subpathway and enriched Transcription Factors.'

@@ -808,7 +808,7 @@ res <- organismVisualization(

                     verbose=FALSE)

 ```

-```{r, echo=FALSE, fig.width=7.4, fig.height=6, fig.cap=cap}

+```{r, echo=FALSE, fig.width=7.4, fig.height=6, fig.align='center', fig.cap=cap, fig.pos='h', out.extra=''}

 cap <- 'Dot plot shows the enriched associations among experiment-specific 

 extracted subpathways and pathwaysfrom KEGG database.