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ProjectionStructureUnionize data is used in the web application to display projection summary bar graphs.    
   

Comparing Projection Data Grids and Gene Expression Grids

Due to section sampling density, projection data grids are at 100µm resolution while gene expression grids are at 200µm
resolution. Upsampling with appropriate interpolation of the gene expression data is necessary in order to numerically
compare between the two different types of data.  When interpolating the data, "no data" (-1) voxels needs to be handled
specifically.

Example Matlab code snippet to upsample gene expression grid with "no data" handling:

    % Download and unzip energy volume file for gene Rasd2 coronal SectionDataSet 73636089
    mkdir('Rasd2_73636089');
    urlwrite('http://api.brain-map.org/grid_data/download/74819249?include=density', 'temp.zip');
    unzip('temp.zip','Rasd2_73636089');

    % Download and unzip density volume file for BLAa injection SectionDataSet 113144533
    mkdir('BLAa_113144533');
    urlwrite('http://api.brain-map.org/grid_data/download/113144533?include=density', 'temp.zip');
    unzip('temp.zip','BLAa_113144533');

&nbsp;&nbsp;&nbsp; %<span style="color: #339966">% Gene expression grids are at 200 micron resolution.</span>
&nbsp;&nbsp;&nbsp; geneGridSize = \[67 41 58\];
&nbsp;&nbsp;&nbsp; fid = fopen('Rasd2_73636089/density.raw', 'r', 'l'&nbsp; );
&nbsp;&nbsp;&nbsp; Rasd2 = fread( fid, prod(geneGridSize), 'float' );
&nbsp;&nbsp;&nbsp; fclose(fid);
&nbsp;&nbsp;&nbsp; Rasd2 = reshape( Rasd2, geneGridSize );

&nbsp;&nbsp;&nbsp; % <span style="color: #339966">% Projection grids are at 100 micron resolutionresolution</span>
&nbsp;&nbsp;&nbsp; projectionGridSize = \[133 81 115\];
&nbsp;&nbsp;&nbsp; fid = fopen('BLAa_113144533/density.raw', 'r', 'l'&nbsp; );
&nbsp;&nbsp;&nbsp; BLAa = fread( fid, prod(projectionGridSize), 'float' );
&nbsp;&nbsp;&nbsp; fclose(fid);
&nbsp;&nbsp;&nbsp; BLAa = reshape( BLAa, projectionGridSize );

&nbsp;&nbsp;&nbsp; % <span style="color: #339966">% Upsample gene expression grid to same dimension as projection grid using linear interpolationinterpolation</span>
&nbsp;&nbsp;&nbsp; \[xi,yi,zi\] = meshgrid(1:0.5:41,1:0.5:67,1:0.5:58); %note: matlab transposes x-y
&nbsp;&nbsp;&nbsp; d = Rasd2; d(d<0) = 0; % fill in missing data as zeroes
&nbsp;&nbsp;&nbsp; Rasd2_100 = interp3(d ,xi,yi,zi,'linear');

    % Handle "no data" (-1) voxels.
    % Create a mask of "data" vs "no data" voxels and apply linear interpolation
    m = (Rasd2  >= 0); mi = interp3(m,xi,yi,zi,'linear');

    % Normalize data by dividing by interpolated mask. Assign value of "-1" to "no data" voxels.
    Rasd2_100 = Rasd2_100 ./ mi;
    Rasd2_100( mi <= 0 ) = -1;

&nbsp;&nbsp;&nbsp; % <span style="color: #339966">% Create a merged image of one coronal plane;</span>
&nbsp;&nbsp;&nbsp; gimg = squeeze(Rasd2_100(52,:,\:)); gimg = max(0,gimg); gimg = gimg / 0.025; gimg = min(1,gimg);
&nbsp;&nbsp;&nbsp; pimg = squeeze(BLAa(52,:,\:)); pimg = max(0,pimg); pimg = pimg / 0.8; pimg = min(1,pimg);
&nbsp;&nbsp;&nbsp; rgb = zeros(\[size(gimg),3\]); rgb(:,:,1) = gimg; rgb(:,:,2) = pimg;
&nbsp;&nbsp;&nbsp; figure; image(rgb);

<img width="800px" src="/images/UpsampleGeneExpressionGrid.jpg" />

*Image Added

Figure:* ISH SectionDataSet (id=73636089) for gene Rasd2 showing enriched expression in the striatum (left).
Projection SectionDataSet (id=73636089) with injection in the anterior part of the basolateral amygdalar nucleus (BLAa)
showing projection to the striatum and other brain areas (center). One coronal slice of the BLAa projection density grid
(green) merged with an upsampled and interpolated Rasd2 expression density grid (red).<a href="#" onmouseover="hover" title="Back to top"><img width="18px" height="20px" src="/images/back_to_top.png" /></a>