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v0.4.12 - Update Brain Parcellation Projects and Pre-push Hook
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Why:

Yeo2011_fcMRI_clustering
1. Add project-specific prefix Yeo2011 for two scripts of Yeo2011_fcMRI_clustering: 1000subjects_reference/Yeo_JNeurophysiol11_SplitLabels/scripts/CBIG_DownsampleMNI1mmParcellationTo2mm.csh and 1000subjects_reference/Yeo_JNeurophysiol11_SplitLabels/scripts/CBIG_ProjectSplitLabels2MNI1mm.m, which were missing in release v0.4.10.
2. Move example subjects from $CBIG_CODE_DIR/data/example_data/${subj_ID} to $CBIG_CODE_DIR/data/example_data/Corr_HNU/${subj_ID}
3. The example subjects are re-processed by a newer version of our preprocessing pipeline (v0.4.9). Hence results in ./examples are updated.
4. Update some README.md files.

Scaefer2018_LocalGlobal
1. Move example subjects from $CBIG_CODE_DIR/data/example_data/${subj_ID} to $CBIG_CODE_DIR/data/example_data/Corr_HNU/${subj_ID}.
2. The example subjects are re-processed by a newer version of our preprocessing pipeline (v0.4.9). Hence results in ./Code/examples are updated.
3. Update some README.md files.

Pre-push hook:
1. Add checking for unit_tests folder in each stable project.
2. Remove exclusion for Scaefer2018_LocalGlobal, Yeo2011_fcMRI_clustering, Liegeois2017_Surrogates projects.

This change addresses the need by:

* All users
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Li Jingwei committed Apr 9, 2018
1 parent 72eca7d commit ed48940
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37 changes: 37 additions & 0 deletions data/example_data/CoRR_HNU/README.md
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This folder contains subjects from the preprocessed CoRR_HNU dataset. We use these subjects as example data so that people can run our example code and make sure the outputs are correct.

----

CoRR_HNU dataset
================
The CoRR_HNU dataset is an open source science resource created by CoRR (Consortium for Reliability and Reproducibility). We get permission from Professor Xi-Nian Zuo to re-release a few preprocessed CoRR_HNU subjects here as example data.

You may refer to this paper for more information about the CoRR_HNU dataset: [An open science resource for establishing reliability and reproducibility in functional connectomics](https://www.nature.com/articles/sdata201449.pdf).

----

CBIG preprocessing pipeline
===========================
Example data from the CoRR_HNU dataset have been preprocessed with our CBIG pipeline (version number v0.4.9).

The order of preprocessing steps are listed below:

* CBIG_preproc_skip -skip 4

* CBIG_preproc_fslslicetimer -slice_order ${CBIG_CODE_DIR}/stable_projects/preprocessing/CBIG_fMRI_Preproc2016/example_slice_order.txt

* CBIG_preproc_fslmcflirt_outliers -FD_th 0.2 -DV_th 50 -discard-run 50 -rm-seg 5 -spline_final

* CBIG_preproc_bbregister -intrasub_best

* CBIG_preproc_regress -whole_brain -wm -csf -motion12_itamar -detrend_method detrend -per_run -censor -polynomial_fit 1

* CBIG_preproc_censor -max_mem NONE

* CBIG_preproc_bandpass -low_f 0.009 -high_f 0.08 -detrend

* CBIG_preproc_QC_greyplot -FD_th 0.2 -DV_th 50

* CBIG_preproc_native2fsaverage -proj fsaverage6 -sm 6 -down fsaverage5


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14 changes: 13 additions & 1 deletion hooks/pre-push
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Expand Up @@ -238,7 +238,7 @@ echo " [PASSED]"
# 4. (files in stable_projects/xxx/xxx (exclude Thomas, Alex, Gia, Xiuming, Raphael))[.m, .c, .cpp, .sh, .csh, .py, .pl, .r]
######
EXTENSIONS_TO_CHECK=("m" "c" "cpp" "sh" "csh" "py" "pl" "r")
EXCLUDED_DIRECTORIES=("Yeo2011_fcMRI_clustering" "Schaefer2018_LocalGlobal" "Zhang2016_ADFactors" "Liegeois2017_Surrogates")
EXCLUDED_DIRECTORIES=("Zhang2016_ADFactors")

echo -e "\n==> [Check 4] Checking stable_projects/xxx/xxx"
for project_path in $CBIG_CODE_DIR/stable_projects/*/*
Expand Down Expand Up @@ -358,6 +358,18 @@ tested to work."
fi
echo " [PASSED]"
fi

###
# check whether all projects have the unit_tests folder
###
echo -e "\n====> Check whether this project has unit_tests folder"
if [ ! -d "$project_path/unit_tests" ]; then
echo " [FAILED] $project_path does not have a unit_tests folder"
echo "Please add a unit_tests folder under $project_path manually"
exit 1
fi
echo " [PASSED]"

done
exit 0

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10 changes: 5 additions & 5 deletions setup/Release_Public/README.md
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Expand Up @@ -4,11 +4,6 @@ Zhang XM, Mormino EC, Sun N, Sperling RA, Sabuncu MR, Yeo BTT. [**Bayesian model

----

## Updates
- Release vx.x.x (dd/mm/yyyy): Description

----

## Data Release [This section is Optional]
The data utilized in this study are released in `XXXXDataRelease` folder. Specifically, the data include:
- Describe your data
Expand Down Expand Up @@ -36,6 +31,11 @@ git checkout -b LastName20yy_ProjectName vx.x.x-LastName20yy_ProjectName

----

## Updates
- Release vx.x.x (dd/mm/yyyy): Description

----

## Bugs and Questions

Please contact FirstAuthor at FirstAuthor_email_address and Thomas Yeo at yeoyeo02@gmail.com.
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Expand Up @@ -5,7 +5,6 @@ Here we provide an example for you to run so that you can have a brief sense abo
References
==========
+ Schaefer A, Kong R, Gordon EM, Zuo XN, Holmes AJ, Eickhoff SB, Yeo BT, (accepted), Local-Global Parcellation of the Human Cerebral Cortex From Intrinsic Functional Connectivity MRI, Cerebral Cortex
+ Zuo, X.N., et al (2014), An open science resource for establishing reliability and reproducibility in functional connectomics, Sci data, 1:140049

----

Expand All @@ -21,7 +20,8 @@ Please follow the instructions in `<your-cbig-repo-direcotry>/setup/README.md` t

Example data
============
We use two subjects from the preprocessed Hangzhou Normal University (HNU) dataset as example data. The example data can be found here: `${CBIG_CODE_DIR}/data/example_data`.
We use two subjects from the preprocessed CoRR_HNU dataset as example data. The example data can be found here: `<your-cbig-repo-direcotry>/data/example_data/CoRR_HNU`.
For more information on the CoRR_HNU dataset, you may refer to this paper by Xi-Nian Zuo et al.: [An open science resource for establishing reliability and reproducibility in functional connectomics](https://www.nature.com/articles/sdata201449.pdf).

----

Expand Down Expand Up @@ -87,7 +87,7 @@ Our figure for seed 2 is provided here:

Please note that the example clustering results may not look good since only two subjects are applied. The parameter settings are also simple to achieve shorter running time.

In our paper we use 1489 subjects' resting state fMRI data from the GSP dataset. Please refer to the paper and supplementary data for more information about the data and parameters we use.
In our paper we use 1489 subjects' resting state fMRI data from the GSP data set. Please refer to the paper and [supplementary material](https://academic.oup.com/cercor/advance-article/doi/10.1093/cercor/bhx179/3978804?searchresult=1) for more information about the data and parameters we use.

----

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#!/bin/bash

# This simple script creates a list that contains the full paths to example subjects's surf data. Each line is one subject with different runs.
# Assume that the folder structure of CBIG_private respository is preserved and not changed.
# This simple script creates a list that contains the full paths to example subjects' surf data. Each line represents one subject with different runs.
# Assume the folder structure of CBIG respository is preserved
# Written by CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md



# set paths
data_dir=${CBIG_CODE_DIR}/data/example_data
# Set paths
data_dir=${CBIG_CODE_DIR}/data/example_data/CoRR_HNU

output_dir=${1}
mkdir -p ${output_dir}

# create a file to store example full paths

# Create a file to store example full paths
output_file="${output_dir}/example_input_fullpaths.csv"
touch ${output_file}


# write the full paths to example subjects's surf data. Each line is one subject with different runs.
echo -n "${data_dir}/subj01/subj01_sess1/surf/lh.subj01_sess1_bld002_rest_skip4_stc_mc_resid_cen_FDRMS0.2_DVARS50_bp_0.009_0.08_fs6_sm6.nii.gz " > ${output_file}
echo -e "${data_dir}/subj01/subj01_sess2/surf/lh.subj01_sess2_bld002_rest_skip4_stc_mc_resid_cen_FDRMS0.2_DVARS50_bp_0.009_0.08_fs6_sm6.nii.gz" >> ${output_file}
# Write full paths to example subjects' surf data, each line represents one subject with different runs
echo -n "${data_dir}/subj01/subj01_sess1/surf/lh.subj01_sess1_bld002_rest_skip4_stc_mc_residc_interp_FDRMS0.2_DVARS50_bp_0.009_0.08_fs6_sm6.nii.gz " > ${output_file}
echo -e "${data_dir}/subj01/subj01_sess2/surf/lh.subj01_sess2_bld002_rest_skip4_stc_mc_residc_interp_FDRMS0.2_DVARS50_bp_0.009_0.08_fs6_sm6.nii.gz" >> ${output_file}

echo -n "${data_dir}/subj02/subj02_sess1/surf/lh.subj02_sess1_bld002_rest_skip4_stc_mc_resid_cen_FDRMS0.2_DVARS50_bp_0.009_0.08_fs6_sm6.nii.gz " >> ${output_file}
echo -e "${data_dir}/subj02/subj02_sess2/surf/lh.subj02_sess2_bld002_rest_skip4_stc_mc_resid_cen_FDRMS0.2_DVARS50_bp_0.009_0.08_fs6_sm6.nii.gz" >> ${output_file}
echo -n "${data_dir}/subj02/subj02_sess1/surf/lh.subj02_sess1_bld002_rest_skip4_stc_mc_residc_interp_FDRMS0.2_DVARS50_bp_0.009_0.08_fs6_sm6.nii.gz " >> ${output_file}
echo -e "${data_dir}/subj02/subj02_sess2/surf/lh.subj02_sess2_bld002_rest_skip4_stc_mc_residc_interp_FDRMS0.2_DVARS50_bp_0.009_0.08_fs6_sm6.nii.gz" >> ${output_file}


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