Input formats¶
Currently supported
- Freesurfer
- Subcortical volumes
- Wholebrain Aseg stats
- Arbitary/user-defined format (see below)
In development (stay tuned)
- Freesurfer
- cortical thickness
- gray matter density
- structural covariance
- Any nibabel-readable data
- DT-MRI features
- task-free fMRI features
- HCP datasets
- Weka’s ARFF format
Interfaces to Neuroimaging tools¶
neuropredict is aimed at interfacing with popular feature extraction algorithms such as Freesurfer, FSL and others directly - see Readers section below. However, it allows an arbitray input of features that have already been extracted via user’s own pipeline(s).
Arbitray feature input¶
For custom input:
- the user needs to save the features in a single folder for all subjects (let’s call it
/project/myawsomepipeline
) - specify it with –userdefined /project/myawsomepipeline
- the user needs to save the features in a single folder for all subjects (let’s call it
- within which, features for each subject in a separate folder (named after its id specified in the meta data file)
- in a file called
features.txt
. Thefeatures.txt
file must contain a single floating point number per line (see below - its not comma separated), - and all the subject features must have an equal number of features.
Then neuropredict will automatically consolidate the features into its native pyradigm MLdataset format, ideally suited for the predictive analysis tasks.
The example for a dataset with 2 controls and 2 disease sujects with 5 features each is shown below:
$ 11:19:22 linux userdefined >> ls -1
control-001
control-002
disease-003
disease-004
$ 11:19:30 linux userdefined >> tree
.
|-- control-001
| `-- features.txt
|-- control-002
| `-- features.txt
|-- disease-003
| `-- features.txt
`-- disease-004
`-- features.txt
4 directories, 4 files
$ 11:19:33 linux userdefined >> head -n 5 */features.txt
==> control-001/features.txt <==
0.868896136902
0.542305564899
0.115903893374
0.503297862357
0.564961631104
==> control-002/features.txt <==
0.868896136902
0.542305564899
0.115903893374
0.503297862357
0.564961631104
==> disease-003/features.txt <==
0.868896136902
0.542305564899
0.115903893374
0.503297862357
0.564961631104
==> disease-004/features.txt <==
0.868896136902
0.542305564899
0.115903893374
0.503297862357
0.564961631104