permutations tmaps different from fsl randomize output by a factor of ~470

[egillax]

Thank you for the great toolbox!

I'm getting different results for the t-maps outputted by BROCCOLI's RandomiseGroupLevel and fsl randomise where I'm only testing for the groupmean (-groupmean flag in Broccoli and -1 flag in randomise).

The commands I ran were: RandomiseGroupLevel volumes.nii -groupmean randomise -i volumes.nii -o output -1

The maps look the same but the t-values are off by a factor of ~470 for BROCCOLI. So like 0.06 instead of 28. I've also done a 1 sample t-test in spm and the results are very similar to the randomise ones.

I've attached the information about my system from getOpenCLInfo.

I can put the data on dropbox for you if you wan't to try it out yourself. Any idea what could be the problem?

CLI_info.txt

[wanderine]

That sounds strange, if you put the data on dropbox I can try it.

2017-09-21 16:53 GMT+02:00 egillax notifications@github.com:

Thank you for the great toolbox!

I'm getting different results for the t-maps outputted by BROCCOLI's RandomiseGroupLevel and fsl randomise where I'm only testing for the groupmean (-groupmean flag in Broccoli and -1 flag in randomise).

The commands I ran were: RandomiseGroupLevel volumes.nii -groupmean randomise -i volumes.nii -o output -1

The maps look the same but the t-values are off by a factor of ~470 for BROCCOLI. So like 0.06 instead of 28. I've also done a 1 sample t-test in spm and the results are very similar to the randomise ones.

I've attached the information about my system from getOpenCLInfo.

I can put the data on dropbox for you if you wan't to try it out yourself. Any idea what could be the problem?

CLI_info.txt https://github.com/wanderine/BROCCOLI/files/1321624/CLI_info.txt

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[egillax]

Here it is:

https://www.dropbox.com/s/80818jjv5n7m81r/volumes.nii?dl=0

[wanderine]

There is something strange in the header. If I do

fslinfo volumes.nii

it says that the data_type is UINT8, but if I look at the dataset in fslview

fslview volumes.nii

the values are actually floats... so if I do

fslmaths volumes.nii volumes_float.nii -odt float

and then run RandomiseGroupLevel the t-scores are much higher

2017-09-21 20:18 GMT+02:00 egillax notifications@github.com:

Here it is:

https://www.dropbox.com/s/80818jjv5n7m81r/volumes.nii?dl=0

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-- Anders Eklund, PhD

[egillax]

Thanks! That did the trick.