### License Info

This program is free software: you can redistribute it and/or modify it
under the terms of the GNU General Public License as published by the
Free Software Foundation, either version 3 of the License, or (at your
option) any later version.

This program is distributed in the hope that it will be useful, but
WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General
Public License for more details.

Please check <http://www.gnu.org/licenses/>.

The code included in the present notebook is based on this
[script](https://git-r3lab.uni.lu/computational-modelling-and-simulation/generegulationanalysis/-/blob/master/5_SBMLSearch/SourceCode/grep_disease_map.R)
developed by Yusuke Hiki

Introduction
============

The present script takes the output of our Footprint-based analysis and
matches the results againts the content of [the Covid-19 Disease
Maps](https://covid.pages.uni.lu/map_contents)

    library(kableExtra)

Results
=======

Reading Input files
-------------------

We first read the content ofthe Covid-19 Disease Maps which can be found
in this
[file](https://gitlab.lcsb.uni.lu/covid/models/-/blob/master/Resources/Expand%20the%20diagrams/COVID19_Disease_Map_bipartite_crosslinked_additional_HGNCs.tsv):

    disease_map <- read.delim("https://gitlab.lcsb.uni.lu/covid/models/-/raw/master/Resources/Expand%20the%20diagrams/COVID19_Disease_Map_bipartite_crosslinked_additional_HGNCs.tsv")

    # Extract row with HGNC symbol
    disease_map_hgnc <- disease_map[ !is.na( disease_map$source_hgnc ), ]

    # Get HGNC symbol list for each row
    disease_map_gene_list <- strsplit( x=gsub( pattern="HGNC_SYMBOL:", replacement="", x=disease_map_hgnc$source_hgnc ), split=";" )

We then read the output of our Footprint-based analyisis, namely
CARNIVAL's output network. This file can be found
[here](https://gitlab.lcsb.uni.lu/computational-modelling-and-simulation/footprint-based-analysis-and-causal-network-contextualisation-in-sars-cov-2-infected-a549-cell-line/-/tree/master/Carnival_Results).

    carnival_results <- readRDS("InputFiles/carnival_results_withprogeny.rds")
    carnival_nodes_hgnc <- unique(c(carnival_results$weightedSIF[,"Node1"], carnival_results$weightedSIF[,"Node2"]))

Matching the results
--------------------

We finally match all our genes from the carnival network with all the
genes from the different pathways included in the COVID19 Disease maps.

    disease_map_hgnc_carnival_detected <- data.frame()


    for( current_gene in  carnival_nodes_hgnc){
      
      # Get row index of disease map matched with target gene
      index_matched <- which( unlist( lapply( X=disease_map_gene_list, FUN=function(x){ return( any(current_gene==x) ) } ) ) )
      
      # Extract the row
      if( length( index_matched ) != 0 ){
        disease_map_hgnc_carnival_detected_i <- cbind( disease_map_hgnc[ index_matched, ], hgnc_carnival=current_gene )
        disease_map_hgnc_carnival_detected <- rbind( disease_map_hgnc_carnival_detected, disease_map_hgnc_carnival_detected_i )
      }
    }

    disease_map_hgnc_carnival_detected <- unique( disease_map_hgnc_carnival_detected[ ,c("source_diagram", "hgnc_carnival") ] )
    rownames(disease_map_hgnc_carnival_detected) <- NULL

and We visualize the results.

    disease_map_hgnc_carnival_detected %>% 
      kbl(col.names = c("Covid19 DM Diagram", "Carnival nodes")) %>% 
      kable_styling()

<table class="table" style="margin-left: auto; margin-right: auto;">
<thead>
<tr>
<th style="text-align:left;">
Covid19 DM Diagram
</th>
<th style="text-align:left;">
Carnival nodes
</th>
</tr>
</thead>
<tbody>
<tr>
<td style="text-align:left;">
C19DMap:PAMP signalling
</td>
<td style="text-align:left;">
TICAM1
</td>
</tr>
<tr>
<td style="text-align:left;">
C19DMap:Orf3a protein interactions
</td>
<td style="text-align:left;">
TICAM1
</td>
</tr>
<tr>
<td style="text-align:left;">
C19DMap:TGFbeta signalling
</td>
<td style="text-align:left;">
MAPK3
</td>
</tr>
<tr>
<td style="text-align:left;">
C19DMap:Interferon 1 pathway
</td>
<td style="text-align:left;">
TBK1
</td>
</tr>
<tr>
<td style="text-align:left;">
C19DMap:PAMP signalling
</td>
<td style="text-align:left;">
TBK1
</td>
</tr>
<tr>
<td style="text-align:left;">
C19DMap:Pyrimidine deprivation
</td>
<td style="text-align:left;">
TBK1
</td>
</tr>
<tr>
<td style="text-align:left;">
C19DMap:Interferon lambda pathway
</td>
<td style="text-align:left;">
TBK1
</td>
</tr>
<tr>
<td style="text-align:left;">
C19DMap:Endoplasmatic Reticulum stress
</td>
<td style="text-align:left;">
ATF6
</td>
</tr>
<tr>
<td style="text-align:left;">
C19DMap:Interferon 1 pathway
</td>
<td style="text-align:left;">
IKBKE
</td>
</tr>
<tr>
<td style="text-align:left;">
C19DMap:PAMP signalling
</td>
<td style="text-align:left;">
IKBKE
</td>
</tr>
<tr>
<td style="text-align:left;">
C19DMap:TGFbeta signalling
</td>
<td style="text-align:left;">
SMAD1
</td>
</tr>
<tr>
<td style="text-align:left;">
C19DMap:Endoplasmatic Reticulum stress
</td>
<td style="text-align:left;">
ATF4
</td>
</tr>
<tr>
<td style="text-align:left;">
C19DMap:Endoplasmatic Reticulum stress
</td>
<td style="text-align:left;">
MBTPS1
</td>
</tr>
<tr>
<td style="text-align:left;">
C19DMap:Interferon 1 pathway
</td>
<td style="text-align:left;">
IRF3
</td>
</tr>
<tr>
<td style="text-align:left;">
C19DMap:PAMP signalling
</td>
<td style="text-align:left;">
IRF3
</td>
</tr>
<tr>
<td style="text-align:left;">
C19DMap:Pyrimidine deprivation
</td>
<td style="text-align:left;">
IRF3
</td>
</tr>
<tr>
<td style="text-align:left;">
C19DMap:Interferon lambda pathway
</td>
<td style="text-align:left;">
IRF3
</td>
</tr>
</tbody>
</table>
Session Info Details
====================

    ## R version 4.0.4 (2021-02-15)
    ## Platform: x86_64-w64-mingw32/x64 (64-bit)
    ## Running under: Windows 10 x64 (build 19042)
    ## 
    ## Matrix products: default
    ## 
    ## locale:
    ## [1] LC_COLLATE=English_Germany.1252  LC_CTYPE=English_Germany.1252   
    ## [3] LC_MONETARY=English_Germany.1252 LC_NUMERIC=C                    
    ## [5] LC_TIME=English_Germany.1252    
    ## 
    ## attached base packages:
    ## [1] stats     graphics  grDevices utils     datasets  methods   base     
    ## 
    ## other attached packages:
    ## [1] kableExtra_1.3.4
    ## 
    ## loaded via a namespace (and not attached):
    ##  [1] rstudioapi_0.13   knitr_1.33        xml2_1.3.2        magrittr_2.0.1   
    ##  [5] rvest_1.0.0       munsell_0.5.0     colorspace_2.0-1  viridisLite_0.4.0
    ##  [9] R6_2.5.1          rlang_0.4.11      highr_0.9         stringr_1.4.0    
    ## [13] httr_1.4.2        tools_4.0.4       webshot_0.5.2     xfun_0.24        
    ## [17] htmltools_0.5.1.1 systemfonts_1.0.2 yaml_2.2.1        digest_0.6.27    
    ## [21] lifecycle_1.0.1   glue_1.4.2        evaluate_0.14     rmarkdown_2.9    
    ## [25] stringi_1.6.2     compiler_4.0.4    scales_1.1.1      svglite_2.1.0