Fast and memory efficient approach for connectome-wide association studies in R and C++. Uses custom implementation of multivariate distance matrix regression to associate brain and behavior.
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Using CWAS for Structural Connectivity Matrices #11
Dear Zarrar Shehzad
I want to use the package Connectir to do CWAS, but I already have my structural matrices(based on 1000 parcellations) and my behavioural score. So I have to skip the steps regarding creating connectivity matrices etc. The problem I have is that I don't know how to prepare my data for MDMR.
Base on one of your suggestions for those who dont want to do intense voxel-based computation, I downloaded https://github.com/czarrar/connectir/files/3325747/Rmdmr.zip . But in the rscript "Rmdmr/242_parcellate_sm/20_mdmr.R"
but for example there are some files like id_controls.txt that I dont know how they are prepared.
I wonder if you have a sample model for your score file or the output of connectivity part (the input of MDMR) so I see how to prepare my own data?
I would be grateful if you help me with that.
Best regards
Maedeh
Dear Zarrar Shehzad I want to use the package Connectir to do CWAS, but I already have my structural matrices(based on 1000 parcellations) and my behavioural score. So I have to skip the steps regarding creating connectivity matrices etc. The problem I have is that I don't know how to prepare my data for MDMR. Base on one of your suggestions for those who dont want to do intense voxel-based computation, I downloaded https://github.com/czarrar/connectir/files/3325747/Rmdmr.zip . But in the rscript "Rmdmr/242_parcellate_sm/20_mdmr.R" but for example there are some files like id_controls.txt that I dont know how they are prepared. I wonder if you have a sample model for your score file or the output of connectivity part (the input of MDMR) so I see how to prepare my own data? I would be grateful if you help me with that. Best regards Maedeh