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repo setup

Max Pietsch 3 years ago
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README.md

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-# dHCP_neonatal_HARDI_atlas
+![tracking performed on the A0 component overlaid onto the tissue component ODFs](components.png)
+# dHCP neonatal-multi-component-HARDI-atlas
 
-dHCP neonatal multi-component HARDI atlas
+This hosts the multi-component atlas of diffusion MRI data over the neonatal period created for the publication **A framework for multi-component analysis of diffusion MRI data over the neonatal period.**
+doi: [10.1016/j.neuroimage.2018.10.060](https://www.sciencedirect.com/science/article/pii/S1053811918320329)
+using data collected as part of the [developing Human Connectome Project](http://www.developingconnectome.org/) (dHCP).
+
+The weekly templates can be downloaded individually from [here](https://gin.g-node.org/maxpietsch/dHCP_neonatal_HARDI_atlas/src/master/v1/rigid/mean).
+
+
+---
+
+
+To conveniently get local access to all data, I'd recommend using the [GIN-CLI client](http://https://github.com/G-Node/gin-cli).
+
+On macOS, it can be installed via [homebrew](https://brew.sh/):
+```bash
+brew tap g-node/pkg
+brew install g-node/pkg/gin-cli
+```
+
+On ubuntu:
+```bash
+wget https://web.gin.g-node.org/G-Node/gin-cli-releases/raw/master/gin-cli-latest.deb
+sudo dpkg -i gin-cli-latest.deb
+sudo apt install -f
+```
+
+For standlone binaries and instructions for other operating systems, see [here](https://github.com/G-Node/gin-cli/wiki/downloads).
+
+
+Then, to download this repository simply execute
+```bash
+gin get maxpietsch/dHCP_neonatal_HARDI_atlas
+cd dHCP_neonatal_HARDI_atlas
+```
+
+Initially, place-holder files are downloaded instead of larger files (.git/annex). If you want to download all files use `gin download --content`, for individual files or directories use `gin get-content <location>`, for downloading all rigidly aligned templates use `gin get-content v1/rigid/mean`, check the download status with `gin ls`. See [GIN CLI Usage Tutorial](https://gin.g-node.org/G-Node/Info/wiki/GIN+CLI+Usage+Tutorial) for details.
+
+
+This repo is organised hierarchically: 
+
+
+```
+├── LICENSE
+├── README.md
+└── v1                          <-- atlas version (`v1` is as used for the paper)
+    ├── joint                   <-- jointly aligned data (single space across time)
+    │   ├── mean                <-- mode of aggregation
+    │   ├── median              <-- mode of aggregation
+    │   ├── rois                <-- regions of interest used for the paper
+    ├── rigid                   <-- weekly templates, rigidly aligned
+    │   ├── mean
+    │   └── median
+    └── metadata                <-- subject information and response functions
+        ├── rf_csf_all
+        ├── rf_native
+        ├── rf_tissue_32.9
+        ├── rf_tissue_44.1
+        ├── sub_ses_ga_32.9
+        ├── sub_ses_ga_34.0
+        ├── sub_ses_ga_35.2
+        ├── sub_ses_ga_35.7
+        ├── sub_ses_ga_37.1
+        ├── sub_ses_ga_38.1
+        ├── sub_ses_ga_39.1
+        ├── sub_ses_ga_40.1
+        ├── sub_ses_ga_40.9
+        ├── sub_ses_ga_42.0
+        ├── sub_ses_ga_42.8
+        └── sub_ses_ga_44.1
+```
+
+The files (see [fig. 3](https://www.sciencedirect.com/science/article/pii/S1053811918320329#fig3)):
+
+```
+
+├── LICENSE
+├── README.md
+└── v1
+    ├── joint
+    │   ├── mean
+    │   │   ├── 32.9
+    │   │   │   ├── adc.mif.gz                         <-- DTI-fit, ADC map
+    │   │   │   ├── count.mif.gz                       <-- sum across masks, useful to modify template mask
+    │   │   │   ├── fa.mif.gz                          <-- DTI-fit, FA map
+    │   │   │   ├── mask.mif.gz
+    │   │   │   ├── odf_csf_normed_cyo.mif.gz          <-- fluid component ODF, intensity, normalised
+    │   │   │   ├── odf_csf_normed_native.mif.gz       <-- subject-native fluid image
+    │   │   │   ├── odf_o_normed_cyo.mif.gz            <-- Ao: older-appearing tissue component
+    │   │   │   ├── odf_wm_gm_normed_native.mif.gz     <-- subject-native tissue image
+    │   │   │   └── odf_y_normed_cyo.mif.gz            <-- Ay: younger-appearing tissue component, normalised
+    │   │   ├── 34.0
+...
+    ├── metadata
+    │   ├── rf_native                                   <-- subject-specific response functions
+    │   │   ├── sub-CC00063AN06_ses-15102_36_csf.txt    <-- CSF response function for this subject (PMA: 36w)
+    │   │   ├── sub-CC00063AN06_ses-15102_36_wm_gmi.txt
+    │   │   ├── sub-CC00065XX08_ses-18600_41_csf.txt
+    │   │   ├── sub-CC00065XX08_ses-18600_41_wm_gmi.txt
+    │   │   ├── sub-CC00067XX10_ses-20200_40_csf.txt
+
+...
+    │   ├── rf_csf_all                                  <-- group-average response functions
+    │   ├── rf_tissue_32.9
+    │   ├── rf_tissue_44.1
+    │   ├── sub_ses_ga_32.9                             <-- subject identitifers per age group
+    │   ├── sub_ses_ga_34.0
+    │   ├── sub_ses_ga_35.2
+    │   ├── sub_ses_ga_35.7
+    │   ├── sub_ses_ga_37.1
+    │   ├── sub_ses_ga_38.1
+    │   ├── sub_ses_ga_39.1
+    │   ├── sub_ses_ga_40.1
+    │   ├── sub_ses_ga_40.9
+    │   ├── sub_ses_ga_42.0
+    │   ├── sub_ses_ga_42.8
+    │   └── sub_ses_ga_44.1
+    └── rigid
+        ├── mean
+        │   ├── 32.9
+        │   │   ├── adc.mif.gz
+        │   │   ├── count.mif.gz
+        │   │   ├── fa.mif.gz
+        │   │   ├── mask.mif.gz
+        │   │   ├── odf_csf_normed_cyo.mif.gz
+        │   │   ├── odf_csf_normed_native.mif.gz
+        │   │   ├── odf_o_normed_cyo.mif.gz
+        │   │   ├── odf_wm_gm_normed_native.mif.gz
+        │   │   └── odf_y_normed_cyo.mif.gz
+        │   ├── 34.0
+...
+```
+
+Note that mean and median aggregation was perfomed using (Not-a-Number-) masked data using the
+brain masks as inclusion criteria for the aggregation operation. This prevents
+bias due to cropped data and allows retrospectively thresholding the template 
+voxels by the number of subjects using the count.mif.gz images. 
+For instance, the following replaces voxels to which fewer than 5 subjects contribute by NaNs:
+`mrcalc count.mif.gz 5 -ge odf_o_normed_cyo.mif.gz nan -if odf_o_normed_cyo_thresholded.mif.gz`
+
+
+You can cite this work:
+
+Pietsch, Maximilian, et al. "A framework for multi-component analysis of diffusion MRI data over the neonatal period." NeuroImage 186 (2019): 321-337.
+
+```bibtex
+@article{pietsch2019framework,
+  title={A framework for multi-component analysis of diffusion MRI data over the neonatal period},
+  author={Pietsch, Maximilian and Christiaens, Daan and Hutter, Jana and Cordero-Grande, Lucilio and Price, Anthony N and Hughes, Emer and Edwards, A David and Hajnal, Joseph V and Counsell, Serena J and Tournier, J-Donald},
+  journal={NeuroImage},
+  volume={186},
+  pages={321--337},
+  year={2019},
+  publisher={Elsevier}
+}
+```

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components.png


+ 77 - 0
datacite.yml

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+# Metadata for DOI registration according to DataCite Metadata Schema 4.1.
+# For detailed schema description see https://doi.org/10.5438/0014
+
+## Required fields
+
+# The main researchers involved. Include digital identifier (e.g., ORCID)
+# if possible, including the prefix to indicate its type.
+authors:
+  -
+    firstname: "Maximilian"
+    lastname: "Pietsch"
+  -
+    firstname: "Daan"
+    lastname: "Christiaens"
+  -
+    firstname: "Jana"
+    lastname: "Hutter"
+  -
+    firstname: "Lucilio"
+    lastname: "Cordero-Grande"
+  -
+    firstname: "Anthony N"
+    lastname: "Price"
+  -
+    firstname: "Emer"
+    lastname: "Hughes"
+  -
+    firstname: "A David"
+    lastname: "Edwards"
+  -
+    firstname: "Joseph V"
+    lastname: "Hajnal"
+  -
+    firstname: "Serena J"
+    lastname: "Counsell"
+  -
+    firstname: "J-Donald"
+    lastname: "Tournier"
+
+
+# A title to describe the published resource.
+title: "Atlas: A framework for multi-component analysis of diffusion MRI data over the neonatal period"
+
+# Additional information about the resource, e.g., a brief abstract.
+description: |
+    A time-resolved group average template of the developing brain. 
+    We decompose advanced multi-shell high angular resolution diffusion imaging data
+    acquired from 113 babies between 33 and 44 weeks postmenstrual age, 
+    imaged as part of the Developing Human Connectome Project,
+    into one isotropic component and two anisotropic components.
+
+# Lit of keywords the resource should be associated with.
+# Give as many keywords as possible, to make the resource findable.
+keywords:
+  - Neuroscience
+  - Diffusion MRI
+  - Brain development
+  - White matter
+  - Atlas
+  
+references:
+    - 
+       id: "doi:10.1016/j.neuroimage.2018.10.060"
+       reftype: "IsSupplementTo"
+       description: "A Framework for Multi-Component Analysis of Diffusion MRI Data Over the Neonatal Period"
+
+# License information for this resource. Please provide the license name and/or a link to the license.
+# Please add also a corresponding LICENSE file to the repository.
+license:
+  name: "CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication"
+  url: "https://creativecommons.org/publicdomain/zero/1.0/"
+
+# Resource type. Default is Dataset, other possible values are Software, DataPaper, Image, Text.
+resourcetype: Dataset
+
+# Do not edit or remove the following line
+templateversion: 1.2