Update README.md

README.md

@@ -74,6 +74,11 @@ 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)
+
 #### Basic analysis
 The **scRNAseq basic** analysis was conducted according to the workflow outlined below:
 
@@ -82,9 +87,15 @@ Normalization (default seurat settings)
 2. ALRA (Imputation with default parameters in RunALRA function)
 2. Scaling (with following variables to regress out: percent.mt + nCount_RNA and CC.Difference calculated as show in [vignette](https://satijalab.org/seurat/articles/cell_cycle_vignette.html#alternate-workflow-1))
 3. Dimensionality reduction: PCA (top 25PCs using 15% most variable genes of whole gene list)
-4. Harmony batch removal (sample/ orig.ident)
+4. Harmony batch removal (timepoint (tp variable) + patient(pt variable))
 5. Clustering (Louvain improved: algorithm number 2 in FindCluster Seurat function)
+6. Markers identification (resolution 0.6 + RefinedAnnotation variable post scGATE annotation with refinement - see scripts below)
+
+#### scGate annotation using Fig2C as reference dataset
+
+
 
+#### WPRE quantification and mapping