Unfortunately, you cannot. We do not prepare the function to retrieve negative correlation for two reasons.
- Multiple probes are often available for a gene. To calculate gene-to-gene correlation between the genes with multiple probes, We use maxinum correlation among all possible probe combination for two genes of interest.
- In general, positive correlation is more useful to suggest gene function than negative correlation.
We know many users have a great interest on the tissue-specific coexpression data. However, we do not have a direct approach to construct them.
To construct tissue-specific coexpression data, we should select the microarray samples for the tissue. On the other hand, to construct reliable coexpression data, we should keep high variety of samples.
As one trial, we extracted genes expressed in a tissue from general coexpression data. Tissue specific-coexpression data on COXPRESdb is constructed like this.
The actual procedure of NetworkDrawer is as follows:
- (1) Searching additional genes.
- (1-1) Checking coexpressed (Top 3 MR) genes from query genes.
- (1-2) Checking PPI genes from query genes. [option]
- (1-3) Summarizing genes with at least two edges to the query genes.
- (2) Making gene network of the genes to draw.
We used "neato" function from Graphviz as follows:
- (1) Prepare a dot file with following parameters.
- overlap=orthoxy;
- model=shortpath;
- start="[regular][1]";
- splines=true;
- fontname=Helvetica;
- node [height=.45, width=.4, fontname=Helvetica];
- (2) Create a postscript file of gene network.
- (3) Parse the postscript file for 2 purposes: (a) to decorate the network easy to see, and (b) to annotate it with KEGG annotation.
- (For small network A)
- (A-4) Convert the postscript fil to PNG file.
- (A-5) Make clickable map on html.
- (For google map network B)
- (B-4) Convert the postscript fil to PNG files with various sizes.
- (B-5) Split each of the PNG files into small rectangle PNG files with 256 x 256 picels.
- (B-6) Use Google Maps API.
Sorry. We do not prepare such function.
; Gene list, 
; Gene network, 
; Download.
