diff --git a/.Rhistory b/.Rhistory
new file mode 100644
index 0000000..e69de29
diff --git a/vignettes/clustSIGNAL_tutorial.Rmd b/vignettes/clustSIGNAL_tutorial.Rmd
index 9f9ad6f..0c4ce35 100644
--- a/vignettes/clustSIGNAL_tutorial.Rmd
+++ b/vignettes/clustSIGNAL_tutorial.Rmd
@@ -3,15 +3,11 @@ title: "clustSIGNAL tutorial"
 author:
   - Pratibha Panwar, Boyi Guo, Haowen Zhou, Stephanie Hicks, Shila Ghazanfar
 date: "`r Sys.Date()`"
-output:
-  BiocStyle::html_document:
-    toc_float: true
-  BiocStyle::pdf_document: default
-package: clustSIGNAL
-vignette: |
-    %\VignetteEngine{knitr::rmarkdown}
-    %\VignetteIndexEntry{clustSIGNAL tutorial}
-    %\VignetteEncoding{UTF-8}
+output: rmarkdown::html_vignette
+vignette: >
+  %\VignetteIndexEntry{clustSIGNAL tutorial}
+  %\VignetteEngine{knitr::rmarkdown}
+  %\VignetteEncoding{UTF-8}
 ---
 
 ```{r, include = FALSE}
@@ -21,6 +17,9 @@ knitr::opts_chunk$set(
   )
 ```
 
+## Section
+
+
 # Overview
 
 In this vignette, we will demonstrate how to perform spatially-resolved clustering with clustSIGNAL. Following this, we will explore the clusters using pre-defined metrics like adjusted rand index (ARI), normalised mutual information (NMI), and average silhouette width, as well as spatial plots. We will also display the use of entropy measures generated as a by-product of clustSIGNAL process in understanding the tissue structure of a sample. In the end, we will also explore multisample analysis with clustSIGNAL.