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Extended readme, fixed datacite.yml

Enrico "erolm_a" Trombetta 1 rok pred
rodič
commit
75bde98903
2 zmenil súbory, kde vykonal 30 pridanie a 7 odobranie
  1. 26 4
      README.md
  2. 4 3
      datacite.yml

+ 26 - 4
README.md

@@ -1,6 +1,28 @@
-# WNt3R_Validation_Data
+# SEB3R Validation Dataset
 
-Data used for the validation of MATLAB pipeline: 
+## About
+
+This repo contains all data used for the validation of MATLAB pipeline: 
 Whisker Nuisance test 3D for Rodents.
-The script are available at the link:
-https://github.com/gchelini87/WNt3R
+The script are available [here](https://gin.g-node.org/gchelini/SEB3R_pipeline).
+
+**Note**: this dataset was generated through DeepLabCut and SEB3R! Original video tracking files are released in
+a [separate](https://gin.g-node.org/gchelini/SEB3R_video_tracking) dataset.
+
+## Usage
+
+- [Download and setup SEB3R](https://gin.g-node.org/gchelini/SEB3R_pipeline#installation)
+- [When launching any script](https://gin.g-node.org/gchelini/SEB3R_pipeline#how-to-use),  use one of the subfolders `WN-HH`, `WN-MH`, or `Open Field group` under `WiN3R results`. All results will be generates within the same subfolder.
+
+## Structure
+
+
+- `WiN3R`: specific dataset groups. Note that they have already been processed with the SEB3R
+  pipeline.
+  - `Open Field group`: mice placed in open field for 15 minutes, divided into 5 3-minute
+    sessions. Used as control.
+  - `WN-MH`: mild habituation group.
+  - `WN-HH`: heavy abituation group.
+  - `Cohort WNt3R validation.xlsx`: summary of the subjects identifiers used in each experimental condition.
+
+- Analyzed Data: a number of statistical tests on the aforementioned datasets performed with GraphPad Prims8 and provided as XLSX file.

+ 4 - 3
datacite.yml

@@ -8,7 +8,7 @@ authors:
     firstname: 'Enrico Maria'
     lastname: Trombetta
     affiliation: 'University of Trento'
-    id: 0000-0001-5162-1059
+    id: orcid:0000-0001-5162-1059
 title: 'SEB3R Validation Data'
 description: 'Dataset supporting SEB3R, a MATLAB pipeline for parcellation of freely-moving mouse behaviour. '
 keywords:
@@ -25,11 +25,12 @@ funding:
 resourcetype: Dataset
 references:
   -
-    id: 'doi:tba'
+    id: 'doi:10.1101/2022.11.27.518077'
     reftype: isDescribedBy
     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'
   -
     id: 'doi:10.12751/g-node.971c6r'
     reftype: isReferencedBy
-    citation: 'Chelini G., Trombetta E. M. (2023) "SEB3R Pipeline"'
+    citation: 'Chelini G., Trombetta E. M. (2023) "SEB3R Pipeline". G-Node. https://doi.org/10.12751/g-node.971c6r'
+'
 templateversion: 1.2