open-discussion
open-discussion > RE: Reproducibility analysis mICA
Mar 27, 2018 02:03 PM | Tawfik Moher Alsady
RE: Reproducibility analysis mICA
Hello Will,
it is possible to use mICA scripts through command line. However, some checks of input correctness might not be performed as they are implemented in the GUI. In addition, you might have to write a wrapper script to automatize the analysis.
For preprocessing, group/single-subject mICA and back-reconstruction you can use the bash scripts in the bin folder, which are documented.
For reproducibility, you have to prepare the randomly splitted groups using splithalf.py
Usage: python splithalf.py list_filename permutations out_prefix
list_filename: path of a text file containing all preprocessed input data (list of nii files)
permutations: is the number of permutation as in the GUI (0 for test-retest)
out_prefix: path of output folder
step 2: is using mica (in bin directory) to perform mICA for each of sampled groups
step 3: calculate correlation using python ic_corr.py in_prefix samples dims [just_read]
in_prefix: path of the folder that contains samples folders (out_prefix of the previous step)
samples: number of samplings
dims: dimensionality range
[just_read]: 0 is default. 1 will not perform fsl_cc and just reads any previously calculated cross-correlation files.
let me know if you need more help.
Greetings,
Tawfik
it is possible to use mICA scripts through command line. However, some checks of input correctness might not be performed as they are implemented in the GUI. In addition, you might have to write a wrapper script to automatize the analysis.
For preprocessing, group/single-subject mICA and back-reconstruction you can use the bash scripts in the bin folder, which are documented.
For reproducibility, you have to prepare the randomly splitted groups using splithalf.py
Usage: python splithalf.py list_filename permutations out_prefix
list_filename: path of a text file containing all preprocessed input data (list of nii files)
permutations: is the number of permutation as in the GUI (0 for test-retest)
out_prefix: path of output folder
step 2: is using mica (in bin directory) to perform mICA for each of sampled groups
step 3: calculate correlation using python ic_corr.py in_prefix samples dims [just_read]
in_prefix: path of the folder that contains samples folders (out_prefix of the previous step)
samples: number of samplings
dims: dimensionality range
[just_read]: 0 is default. 1 will not perform fsl_cc and just reads any previously calculated cross-correlation files.
let me know if you need more help.
Greetings,
Tawfik
Threaded View
Title | Author | Date |
---|---|---|
Will Khan | Mar 22, 2018 | |
Florian Beissner | Mar 22, 2018 | |
Will Khan | Mar 27, 2018 | |
Tawfik Moher Alsady | Mar 27, 2018 | |
Will Khan | Mar 29, 2018 | |
Will Khan | Mar 29, 2018 | |
Tawfik Moher Alsady | Mar 29, 2018 | |
Will Khan | Apr 4, 2018 | |
Tawfik Moher Alsady | Apr 9, 2018 | |
Will Khan | Apr 10, 2018 | |