Update README.md

README.md

@@ -75,9 +75,10 @@ Code details and input for Supplementary Figure 2 can be found in:
 ### Dataset Fig2H
 
 ![Fig2H](https://www.dropbox.com/scl/fi/h3jhl7q67vw74nfh72epx/UMAP_dataset2H.png?rlkey=jkznuqwbs5fqty8wkprbclheq&dl=1) 
+
 Figure 2H: [scGate_Fig2C_dataset_to_Fig2H_dataset.R](http://www.bioinfotiget.it/gitlab/custom/zonari_mpbhscexp_2025/zonari_mpbhscexp_2025_scrnaseq/-/blob/main/scGate_Fig2C_dataset_to_Fig2H_dataset.R). 
 
-Figure 2H: [scGate_Fig2C_dataset_to_Fig2I_dataset.R](http://www.bioinfotiget.it/gitlab/custom/zonari_mpbhscexp_2025/zonari_mpbhscexp_2025_scrnaseq/-/blob/main/scGate_Fig2C_dataset_to_Fig2I_dataset.R)
+Figure 2I: [scGate_Fig2C_dataset_to_Fig2I_dataset.R](http://www.bioinfotiget.it/gitlab/custom/zonari_mpbhscexp_2025/zonari_mpbhscexp_2025_scrnaseq/-/blob/main/scGate_Fig2C_dataset_to_Fig2I_dataset.R)
 
 #### Basic analysis
 The **scRNAseq basic** analysis was conducted according to the workflow outlined below:
@@ -93,6 +94,14 @@ Normalization (default seurat settings)
 
 #### scGate annotation using Fig2C as reference dataset
 
+Cell classification was performed by employing scGATE (v1.6.2) R package (61) using the Fig.2C datasetas reference. In particular we build a gating model by
+using the top 15 positive markers for each population (level 1). For details see [markersdir_scGate_input](http://www.bioinfotiget.it/gitlab/custom/zonari_mpbhscexp_2025/zonari_mpbhscexp_2025_scrnaseq/-/tree/main/markersdir_scGate_input) folder.     
+
+The workflow consists of two steps:
+- building of the model and the raw annotation using scGATE
+- refinement of multiple annotation labels into final label according to custom rules as shown in the code. 
+
+All details can be found in the script [scGate_Fig2C_dataset_to_Fig2H_dataset.R](http://www.bioinfotiget.it/gitlab/custom/zonari_mpbhscexp_2025/zonari_mpbhscexp_2025_scrnaseq/-/blob/main/scGate_Fig2C_dataset_to_Fig2H_dataset.R).  
 
 
 #### WPRE quantification and mapping