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# Locations and Explanations of Variables

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Once a series of image registration methods have been used to bring all = brain images in the study into alignment, the following variables are calcu= lated and put in the 'processed' folder (see "Algorithm Overview"):

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Jacobian - The Jacobian can be used to determine the fa= ctor by which brain regions in the set had to expand or contract in order t= o reach the average of all brains in the study. The Jacobian for a given vo= xel in the brain is a measure based on the deformation of each brain. It ca= n be thought of as the amount by which the volume at that voxel had to be m= ultiplied in order to match the average of all brains in the study. A Jacob= ian of 1 indicates the volume at that voxel matched the average of all brai= ns; a Jacobian that is less than one indicates the volume at that voxel was= greater than the average of all brains; a Jacobian that is greater than on= e indicates the volume at that voxel was less than the average of all brain= s. It is important to note that the Jacobian has been corrected for overall= brain volume.

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Scaled Jacobian - This is equivalent to the Jacobian, e= xcept it has not been corrected for overall brain volume. Therefore, the Sc= aled Jacobian is an absolute measurement while the Jacobian is a relative m= easurement.

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Displacement - Displacement is measured by a vector ext= ending from the initial position to the final position of a voxel. It measu= res the change in position between individual MRIs and the average brain.=20

Magnitude - Magnitude is the size of the displacement v= ector. A larger vector will have a larger magnitude. Likewise, smaller vect= ors will have smaller magnitudes.

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# RMINC Do= wnload and Manuals

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Upon completion of the script, analysis of the data may be conducted usi= ng RMINC. The latest version of RMINC is available at the following website= :

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```https://launchpad.net/rminc
```
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That website also contains a manual called VBMstats.pdf, which practical= ly explains how to use RMINC. A second useful manual named RMINC.pdf is ava= ilable at:

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```www.bic.mni.mcgill.ca/~samir/Brain_imaging/RMINC.pdf
```
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# Creating = a 'Glim' file...

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R must be able to locate where information about each brain is located (= e.g. Jacobians, Scaled Jacobians, etc.). Other pertinent information may al= so be required for analysis such as Weight or Gender. First prepare a simpl= e comma-separated file. In a spreadsheet, input the required data. Some exa= mples of useful variables to include are Mouse ID Number, Weight, Genotype,= Strain, Date of Birth, Gender, Image Number, etc. An example is given belo= w:

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It is important to make sure the labels are exactly the same (including = white spaces and enter spaces), otherwise R will count them as separate cat= egories. For example,
each 'GAMT' above was entered without any extra w= hite spaces at the end. It is also important to be consistent with upper- a= nd lowercase letters. For example, each 'Mutant' above begins with an upper= case letter. Once all information has been entered, save the file as a .csv= file and make sure file name doesn't have white spaces.

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Although the file above specifies the image name, it does not direct R t= o the required information about each image. The user needs to create a scr= ipt which will print into a file full pathways for all required information= . The script must specify level of blur. We recommend either a 1.0 or 0.5 b= lur when looking at total brain structure and volume. This level of blur pr= ovides enough detail for the purposes of looking at total brain. However, w= hen analyzing individual brain structures, we recommend a 0.1 blur instead.= A smaller amount of blur is required because, otherwise, blurring would ru= n over the boundaries of the individual brain structures. The MICe centre i= s happy to forward an example of such a script upon request.

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Once the 'Glim' file is ready, it can be read into R and the user is rea= dy to begin analysis. RMINC is a library which is necessary to read and wri= te MINC data into R. R package can then be used to run linear models, plot = data, etc. Numerous types of analyses are possible in R. The manuals mentio= ned above are a great place to start as they work through practical example= s, employing a variety of analyses.<!-- @page

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