Functions for exporting graph data (a list of connected nodes and corresponding attribute values) for functional neuroimaging data. Currently includes cytoscape and gephi. You must provide a list of anatomical labels (the variable AAL_labels).

cytoscapeExport.m

function cytoscapeExport(links,weights,threshold,exptype)

% This function will take a list of links and weights, and create a file to
% import into Cytoscape for further graph analysis

% exptype is the export type - 'all' means voxelwise above a threshold,
% 'region' means creating graph of average regional values

% links is an n by 2 list of connections, each a voxel id
% weights is a correlation value corresponding to each link set
% You must load AAL_labels, a cell of length 116 with region names, and
% aalflat is a flattened AAL atlas, the same size as the original data

% First write sif file - this is a list of connections between nodes based
% on voxel index

if strcmp(exptype,'all')
    voxels = unique(links(weights>threshold,:),'rows');
    nodes = unique([ voxels(:,1) voxels(:,2) ]);
    weightpt9 = weights(weights>threshold);

    % Write each to file
    filey = fopen('brain.sif','w');
    for v=1:length(voxels)
       fprintf(filey,'%s\n',[ num2str(voxels(v,1)) ' fc ' num2str(voxels(v,2)) ]); 
    end
    fclose(filey);

    % Now create data file that includes region names
    filey = fopen('brain_features.csv','w');
    fprintf(filey,'%s\n','VOXEL,REGION_AAL'); 
    for n=1:length(nodes)
       fprintf(filey,'%s\n',[ num2str(nodes(n)) ',' AAL_labels{aalflat(nodes(n))} ]); 
    end
    fclose(filey);

    % Write edges to file
    filey = fopen('brain_edges.csv','w');
    for v=1:length(voxels)
       fprintf(filey,'%s\n',[ num2str(voxels(v,1)) ' (fc) ' num2str(voxels(v,2)) ' = ' num2str(weightpt9(v)) ]); 
    end
    fclose(filey);

elseif strcmp(exptype,'region')
    
    % Get unique links and weights
    linksA = links(weights>threshold,:);
    weightsA = weights(weights>threshold);
    [linksA,ia,~]  = unique(linksA,'rows');
    weightsA = weightsA(ia);
    
    % Now we need to get rid of duplicates, and also when i==j 
    linksAinv = [ linksA(:,2) linksA(:,1) ];
    dups = (linksA == linksAinv);
    linksA(dups(:,1),:) = [];
    weightsA(dups(:,1)) = [];
    
    % For each region, calculate mean weight
    region_weights = cell(116,116);
    region_vox = zeros(116,116);
    for i=1:116
        for j=1:116
            region_weights{i,j} = [];
        end
    end
    for l=1:length(linksA)
        nodes = sort(aalflat(linksA(l,:)));
                
        % If we have the same region
        region_vox(nodes(1),nodes(2)) = region_vox(nodes(1),nodes(2)) + 1;
        region_weights{nodes(1),nodes(2)} = [ region_weights{nodes(1),nodes(2)}; weightsA(l) ];
    end
    
    % Calculate mean inter and intra region weights
    mean_weights = zeros(116,116);
    for i=1:116
        for j=1:116
            weightset = region_weights{i,j};
            mean_weights(i,j) = mean(weightset(~isnan(weightset)));
        end
    end    
    mean_weights(isnan(mean_weights)) = 0;
    
    % Now write to cytoscape export file
    filey = fopen('brain_region.sif','w');
    for r1=1:116
        for r2=1:116
            region1 = AAL_labels{r1};
            region2 = AAL_labels{r2};
            fprintf(filey,'%s\n',[ region1 ' fc ' region2 ]); 
        end
    end
    fclose(filey);

    % Now create data file that includes intra region weights
    filey = fopen('brain_region_features.csv','w');
    for w1=1:size(mean_weights,1)
        for w2=1:size(mean_weights,2) 
            if w1==w2
                region1 = AAL_labels{w1};
                fprintf(filey,'%s\n',[ region1 ',' num2str(mean_weights(w1,w2)) ]); 
            end
        end
    end
    fclose(filey);

    % Write iter region weights (edges) to file
    filey = fopen('brain_region_edges.csv','w');
    for w1=1:size(mean_weights,1)
        for w2=1:size(mean_weights,2) 
            if w1~=w2
                region1 = AAL_labels{w1};
                region2 = AAL_labels{w2};
                if mean_weights(w1,w2) ~= 0
                fprintf(filey,'%s\n',[ region1 ' (fc) ' region2 ' = ' num2str(mean_weights(w1,w2)) ]); 
                end
            end
        end
    end
    fclose(filey);
      
else
    error('Invalid export type - must specify all or region for fourth argument!');
end

gephiExport.m

function gephiExport(links,weights,threshold)

% This function will take a list of links and weights, and create a file to
% import into gephi for further graph analysis

% links is an n by 2 list of connections, each a voxel id
% weights is a correlation value corresponding to each link set
% You must load AAL_labels, a cell of length 116 with region names, and
% aalflat is a flattened AAL atlas, the same size as the original data

    
    % Get unique links and weights
    linksA = links(weights>threshold,:);
    weightsA = weights(weights>threshold);
    [linksA,ia,~]  = unique(linksA,'rows');
    weightsA = weightsA(ia);
    
    % Now we need to get rid of duplicates, and also when i==j 
    linksAinv = [ linksA(:,2) linksA(:,1) ];
    dups = (linksA == linksAinv);
    linksA(dups(:,1),:) = [];
    weightsA(dups(:,1)) = [];
    
    % For each region, calculate mean weight
    region_weights = cell(116,116);
    region_vox = zeros(116,116);
    for i=1:116
        for j=1:116
            region_weights{i,j} = [];
        end
    end
    for l=1:length(linksA)
        nodes = sort(aalflat(linksA(l,:)));
                
        % If we have the same region
        region_vox(nodes(1),nodes(2)) = region_vox(nodes(1),nodes(2)) + 1;
        region_weights{nodes(1),nodes(2)} = [ region_weights{nodes(1),nodes(2)}; weightsA(l) ];
    end
    
    % Calculate mean inter and intra region weights
    mean_weights = zeros(116,116);
    for i=1:116
        for j=1:116
            weightset = region_weights{i,j};
            mean_weights(i,j) = mean(weightset(~isnan(weightset)));
        end
    end    
    mean_weights(isnan(mean_weights)) = 0;
    
    % Now write to graph wiz export file
    filey = fopen('brain_region.gexf','w');
    fprintf(filey,'%s\n%s\n%s\n%s\n','<gexf xmlns:viz="http:///www.gexf.net/1.1draft/viz" xmlns="http://www.gexf.net/1.1draft" version="1.1">','<meta lastmodifieddate="2010-03-03+23:44">','<creator>Gephi 0.7</creator>','</meta>','<graph defaultedgetype="undirected" idtype="string" type="static">');
    fprintf(filey,'%s\n',[ '<nodes count="' num2str(length(AAL_labels)) '">' ]);
    for r1=1:116
        fprintf(filey,'%s\n',[ 'node id="' num2str(i) '" label="' AAL_labels{r1} '">' ]); 
    end
    fprintf(filey,'%s\n%s\n','</nodes>',[ '<edges count="' num2str(length(links)) '">' ]);
    
    edge_count = 0;
    for r1=1:116
        for r2=1:116
            region1 = AAL_labels{r1};
            region2 = AAL_labels{r2};
            if mean_weights(r1,r2) ~= 0
                fprintf(filey,'%s\n',[ '<edge id="' num2str(edge_count) '" source="' num2str(r1) '" target="' num2str(r2) '" weight="' num2str(mean_weights(r1,r2)) '"/>' ]);
                edge_count = edge_count + 1;
            end    
        end
    end
   fprintf(filey,'%s\n%s\n%s\n','</edges>','</graph>','</gexf>');
   fclose(filey);