Description Usage Arguments Value Examples
View source: R/network_analysis.R
xina_analysis is to analyze protein-protein interaction(PPI) networks using STRINGdb and igraph R package. This module computes PPI networks within each XINA clusters.
| 1 2 3 | xina_analysis(clustering_result, ppi_db, is_stringdb = TRUE,
  flag_simplify = TRUE, node_shape = "sphere",
  num_clusters_in_row = 5, img_size = NULL, img_qual = 300)
 | 
| clustering_result | A list containing XINA clustering results. See xina_clustering | 
| ppi_db | STRINGdb object | 
| is_stringdb | If it is TRUE (default), XINA will process 'ppi_db' as STRINGdb, but it is FALSE, XINA will accepts your 'ppi_db' as it is. You can make your own igraph network using customized PPI information instead of STRINGdb. | 
| flag_simplify | If it is TRUE (default), XINA will exclude unconnected proteins | 
| node_shape | You can choose node shape. Default is "sphere". See shapes | 
| num_clusters_in_row | The number of clusters in a row on the XINA network plot. Default is 5. | 
| img_size | Set the image size. For width=1000 and height=1500, it is img_size=c(1000,1500). | 
| img_qual | Set the image resolution. Default is 300. | 
A PNG file (XINA_Cluster_Networks.png) displaying PPI network plots of all the clusters and a list containing XINA network analysis results.
| Item | Description | 
| All_network | PPI network of all the input proteins | 
| Sub_network | A list containing PPI networks of each clusters | 
| Data | XINA clustering results. See xina_clustering | 
| Nodes | A list of proteins in each cluster | 
| Conditions | A list of experimental condition of proteins in each cluster | 
| Titles | A list of plot titles for XINA plotting | 
| out_dir | A directory path storing XINA network analysis results | 
| is_stringdb | False = different PPI DB and TRUE = STRING DB | 
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ## Not run: 
# load XINA example data
data(xina_example)
# use the following code for utilizing up-to-date STRING DB
tax_id <- 9606  # for human
# tax_id <- 10090  # for mouse
library(STRINGdb)
library(igraph)
string_db <- STRINGdb$new( version='10', species=tax_id, score_threshold=0, input_directory='' )
string_db
xina_result <- xina_analysis(example_clusters, string_db, flag_simplify=FALSE)
# Run XINA with a protein-protein interaction edgelist
data(HPRD)
net_all <- simplify(graph_from_data_frame(d=hprd_ppi, directed=FALSE),
remove.multiple = FALSE, remove.loops = TRUE)
xina_result <- xina_analysis(example_clusters, net_all, is_stringdb=FALSE, flag_simplify=FALSE)
## End(Not run)
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