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help > RE: Remove some matrix value
Mar 26, 2020 11:03 AM | Andrew Zalesky
RE: Remove some matrix value
Hi Li-Ming,
Any connection (pair of regions) that has a connectivity value of 0 for all subjects will be automatically excluded from all statistical testing.
Therefore, in your example, you would only be testing for differences between the regions in the A and C groups.
This does seem to be a bit of an odd thing to do, but it would certainly work.
You might want to test the whole connectivity matrix in case you have omitted any connections in your preliminary analysis.
Andrew
Originally posted by Li-Ming Hsu:
Any connection (pair of regions) that has a connectivity value of 0 for all subjects will be automatically excluded from all statistical testing.
Therefore, in your example, you would only be testing for differences between the regions in the A and C groups.
This does seem to be a bit of an odd thing to do, but it would certainly work.
You might want to test the whole connectivity matrix in case you have omitted any connections in your preliminary analysis.
Andrew
Originally posted by Li-Ming Hsu:
Hi Dr.Zalesky,
Thank you for your help. I have a question about the input matrix.
For each subject, I have a matrix with 100 by 100, which involved 100 brain regions.
By using clustering analysis, the 100 regions can be identified into 5 major group (A, B, C, D, and E).
According to my previous finding, the significant connection change could be found between groupA and groupC.
Now I would like to use NBS as a post-hoc analysis to figure out the significant connection changes within the regions between A and C.
Can I input the 100 by 100 matrix in the NBS and just keep the original connection value between groupA and groupC, but set other connections are zero ?
The 100 by 100 matrix will be like this example below, A1 A2 ... A20 represents 20 regions in group A. In the matrix, the 1 means the original value will be kept.
A1 A2 A3 ... A20 B1 ... B20 C1 C2 C3 ... C20 D1 ... D20 E1 ... D20
A1 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 0 0
A2 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 0 0
... 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 0 0
A20 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 0 0
B1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
B2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
... 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
B20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
C1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
C2 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
C3 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
... 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
C20 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
D1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
... 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
D20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
E1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
... 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
E20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Thanks for your help again.
Best,
Li-Ming
Thank you for your help. I have a question about the input matrix.
For each subject, I have a matrix with 100 by 100, which involved 100 brain regions.
By using clustering analysis, the 100 regions can be identified into 5 major group (A, B, C, D, and E).
According to my previous finding, the significant connection change could be found between groupA and groupC.
Now I would like to use NBS as a post-hoc analysis to figure out the significant connection changes within the regions between A and C.
Can I input the 100 by 100 matrix in the NBS and just keep the original connection value between groupA and groupC, but set other connections are zero ?
The 100 by 100 matrix will be like this example below, A1 A2 ... A20 represents 20 regions in group A. In the matrix, the 1 means the original value will be kept.
A1 A2 A3 ... A20 B1 ... B20 C1 C2 C3 ... C20 D1 ... D20 E1 ... D20
A1 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 0 0
A2 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 0 0
... 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 0 0
A20 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 0 0
B1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
B2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
... 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
B20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
C1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
C2 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
C3 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
... 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
C20 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
D1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
... 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
D20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
E1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
... 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
E20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Thanks for your help again.
Best,
Li-Ming
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| Title | Author | Date |
|---|---|---|
| Li-Ming Hsu | Mar 26, 2020 | |
| Andrew Zalesky | Mar 26, 2020 | |