Add Co Expression Networks
If absolute (log value) transcriptomic datasets are available, you can create a co-expression network through Bacnet interface. Select the datasets which will be taken into account for each genome. Once selected the Pearson correlation between all genes and genome elements available will be calculated and saved in a table. By switching then to bacnet.e4.rap you will be able to visualize the network of co-expression for each gene in a d3.js graphical interface.
If the file CoExpressionNetworks.txt is found with the path indicated on the right of the screen, the list of all the coexpression networks is presented in the table.
Click on Create co-expression Network table, this will create Database/Network/CoExpressionNetworks.txt. this file give the listof genomes for which we have enought transcriptomics datasets to construt co-expression network. You should see now in bacnet.e4.rap.setup the list of genome for which enough transcriptomes datasets are found (check the console to see for which genomes it was created).
Validate co-expression networks by clicking on Validate co-expression networks. Verify that the Validated boxes are checked for each genome. If not click on Add unvalidated co-expression networks. This will take few minutes as it will create all co-expression networks. It calculates pearson correlation, from all transcriptomic datasets, between all genes of a genome.
When everything is computed you can check the results in bacnet.e4.rap. Go in the home page of the website and select Co-Expression Network. For each gene you can display the network of co-expressed elements.
Your database is now organised and contains all necessary files. You can proceed with the deployment of your website.