Update 'README.md'

README.md

@@ -5,13 +5,19 @@ This hosts the multi-component atlas of diffusion MRI data over the neonatal per
 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).
-
 
 ---
 
+## Download 
+
+### Manually
+
+The weekly templates can be downloaded individually from [here](https://gin.g-node.org/maxpietsch/dHCP_neonatal_HARDI_atlas/src/master/v1/rigid/mean).
+
+### via the GIN command line interface
 
-To conveniently get local access to all data, I'd recommend using the [GIN-CLI client](http://https://github.com/G-Node/gin-cli).
+
+This describes how to download the data 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
@@ -37,6 +43,33 @@ 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.
 
+### via Datalad
+
+If needed, install [datalad](https://www.datalad.org/get_datalad.html), then clone this repo with
+
+```bash
+datalad clone https://gin.g-node.org/maxpietsch/dHCP_neonatal_HARDI_atlas
+cd dHCP_neonatal_HARDI_atlas
+```
+
+Finally, download any files needed. For instance, the group-average templates can be downloaded via `datalad get v1/rigid/mean`.
+
+
+
+## Data
+
+Response functions and `.mif.gz` images can be processed, converted and inspected with MRtrix3 (https://www.mrtrix.org/).
+
+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 MRtrix3 command replaces voxel values 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`
+
+
+### Organisation
+
 
 This repo is organised hierarchically: 
 
@@ -132,15 +165,9 @@ The files (see [fig. 3](https://www.sciencedirect.com/science/article/pii/S10538
 ...
 ```
 
-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:
+## Cite
+Please cite the following publication:
 
 Pietsch, Maximilian, et al. "A framework for multi-component analysis of diffusion MRI data over the neonatal period." NeuroImage 186 (2019): 321-337.