Fix typos and missing dataset reference

README.md

@@ -10,6 +10,10 @@ There are very few constraints on the dataset, which are discussed below. [Our p
 
 ## Installation
 
+You should have MATLAB installed, in particular we recommend
+**MATLAB R2023a.** as the tool was tested against this version.
+Octave will **not** work.
+
 First, download or clone this repo.
 
 Secondly, **install the [kmeans_opt](https://it.mathworks.com/matlabcentral/fileexchange/65823-kmeans_opt) package**, by either moving its main module or adding it to MATLAB's search path.
@@ -29,7 +33,7 @@ This is a breakdown of what each step entails:
 
 3. Lastly, re-perform clustering on the newly found BMs. Run `AssignModulesAndQuantify.m`.
 
-4. Optionally, extract the sequence length for each body module of interest. After being propmted a directory for the dataset of interest, it will create a directory
+4. Optionally, extract the sequence length for each body module of interest. After being prompted a directory for the dataset of interest, it will create a directory
 containing all sequencing grouped by experimental condition.
 
 ### Dataset format
@@ -40,11 +44,11 @@ Please make sure your dataset follows the following format:
 
 - Each subject folder follows a purely numeric code, e.g. "123" or "007"; note that "007" and "7" are distinct.
 
-- Each subject folder contains the same set of evaluating condition, named `${SUBJECT}_{CONDITION}_DLC_3D.csv`, for example [058_OF_DLC_3D.csv](https://github.com/gchelini87/SEB3R/blob/main/WN%20results/058/058_OF_DLC_3D.csv). These will be processed in lexicographical order, therefore if you wish to ensure consistent ordering we recommend prefixing them with a number, e.g. `1_Control`, `2_ExperimentalCondition` etc.
+- Each subject folder contains the same set of evaluating condition, named `${SUBJECT}_{CONDITION}_DLC_3D.csv`, for example [058_OF_DLC_3D.csv](https://gin.g-node.org/gchelini/SEB3R_pipeline/src/master/WN%20results/058/058_OF_DLC_3D.csv). These will be processed in lexicographical order, therefore if you wish to ensure consistent ordering we recommend prefixing them with a number, e.g. `1_Control`, `2_ExperimentalCondition` etc.
 
 - Each condition is stored in a CSV matrix as returned by DLC. In particular:
 
-  - Each matrix should have the same header as shown [here](https://github.com/gchelini87/SEB3R/blob/main/WN%20results/058/058_OF_DLC_3D.csv)
+  - Each matrix should have the same header as shown [here](https://gin.g-node.org/gchelini/SEB3R_pipeline/src/master/WN%20results/058/058_OF_DLC_3D.csv)
   
   - Each matrix should have the same number of frames and tracked body parts. **Warning: currently the number of followed body parts is 6 due to instrumental and visual occlusion limitations**. This may change in future releases!
 

datacite.yml

@@ -8,9 +8,9 @@ authors:
     firstname: 'Enrico Maria'
     lastname: Trombetta
     affiliation: 'University of Trento'
-    id: 0000-0001-5162-1059
+    id: ORCID:0000-0001-5162-1059
 title: 'SEB3R Pipeline'
-description: 'A MATLAB pipeline for parcellation of freely-moving mouse behaviour. The tool runs starting from DeepLabCut-3d output files and identifies etnologically-relevant body postures.'
+description: 'A MATLAB pipeline for parcellation of freely-moving mouse behaviour. The tool runs starting from DeepLabCut-3d output files and identifies ethologically-relevant body postures.'
 keywords:
   - Neuroscience
   - 'Murine behaviour'
@@ -24,12 +24,12 @@ funding:
   - 'EU, EU.63,000'
 references:
   -
-    id: 'doi:10.1038/s41596-019-0176-0'
-    reftype: IsReferencedBy
-    citation: "Nath T, Mathis A, Chen AC, Patel A, Bethge M, Mathis (2019) \"Using DeepLabCut for 3D markerless pose estimation across species and\nbehaviors.\" Nature Protocols 14:2152–2176"
-  -
-    id: 'doi:tba'
+    id: 'doi:10.1101/2022.11.27.518077'
     reftype: isSupplementTo
     citation: 'Chelini G., Trombetta E. M., Fortunato-Asquini T., Ollari O., Pecchia T., Bozzi Y. (2023) "Automated Segmentation of the Mouse Body Language to Study Stimulus-Evoked Emotional Behaviors", eNeuro'
-resourcetype: Dataset
+  -
+   id: 'doi:10.12751/g-node.jmy711'
+   reftype: IsReferencedBy
+   citation: 'Chelini G., Trombetta E. M. (2023) SEB3R Validation Data. G-Node. https://doi.org/10.12751/g-node.jmy711'
+resourcetype: Software
 templateversion: 1.2