scilus / connectoflow Goto Github PK

The link in the README pointing to the container list is dead, and the required container is no longer available from the scil's website: https://scil.usherbrooke.ca/pages/containers/

Maybe we should adjust the USAGE of the flow to mimic the latest scil_run_commit.py and suggestions from Simona?

Hello,

I am running Connectoflow for a sample of tumour subjects on Ubuntu 22x04 on a 20 core intel i9 CPU with default settings via Docker, when it gets the Commit2 stage, Commit2 is taking a very long time to run (stuck at 80% at more than 12 h) without any error messages

My data is multishell and I have successfully run Tractoflow prior to this, could this be solved by increasing the NBR_ITR setting?

I have also attached a an example copy of a subject's bvec and bval files

example_bvec.txt

example_bval.txt

My comand is as follows:

NXF_VER=22.10.4 nextflow
run "/input/preproc/ses-1/Connectflow/connectoflow-master/main.nf" -with-docker scilus/scilus:1.2.1_connectoflow-1.1.0 --output_dir "${moving_dir}/input/preproc/ses-${Sessionnum}/Connectflow/output" -profile fully_reproducible --use_commit2 --in_peaks "/input/preproc/ses-${sub_number}/Connectflow/input/S${Sessionnum}/peaks.nii.gz" --input "input/preproc/ses-${Sessionnum}/Connectflow/input" --template "${template_image}" --labels_list "${labels_file}"

Thanks!

Hello,
Thank you so much for creating this great pipeline!
Now I am using Connectoflow pipeline to create networks. For the labels_.nii.gz image, I used the aparc+aseg image (using Desikan-Killiany atlas) from Freesurfer as the labels image. The labels for aparc+aseg image should include cortical and subcortical regions.

In the beginning, for the labels_list, I just used the ctx-regions corresponding integers (10001035,20002035) but I can't get the matrix (the .log file notes that: Empty matrix, no entries to save); at the same time, I found in one of the results files (Average_Connections), which seems to average the streamlines between any pair of two subcortical regions, so the second time I just put the subcortical integers (2,4,5,7,8…,77, 85,251...255) in the label list, and this time I can get the matrix.

I was wondering why the pipeline can not get the connectivity between the cortical regions, or maybe the label image (aparc+aseg) I provided was not the right one?

Thank you so much!

Several of our users are struggling with the .npy output. Should we add an optional .csv or .xlsx output file format option for matrices?

When only using the --processes option (without setting the number of processes for the substeps), Connectoflow crashes if the default value of processes for a given step is higher.
For example, if ran with --processes=6 with the default values for the number of processes for COMMIT (i.e. 8 processes), it will crash when starting commit.
Ideally, when setting --processes, the default value for the different steps should be updated so that they do not exceed the number of CPUs available.