diff --git a/Example_Analysis_Script.py b/Example_Analysis_Script.py
new file mode 100644
index 0000000..95e8889
--- /dev/null
+++ b/Example_Analysis_Script.py
@@ -0,0 +1,50 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Mon Aug 12 18:20:06 2024
+
+@author: jbeckwith
+"""
+
+from src import DAB_Analysis_Functions
+
+DAB_A = DAB_Analysis_Functions.DAB()
+
+overall_directory = "example_directory"
+imtype = ".svs"
+multi_tiff_pixel_size = 4000
+pixel_size = 0.2528e-6
+NA = 0.75
+n_samples_forthresh = 50
+percentile = 90
+giveNN = False
+save_figs = False
+
+"""chop_and_analyse_svs function finds svs files,
+chops them up, analyses them, and then deletes the chopped files
+
+Args:
+    overall_directory (string): directory to search for svs files in sub-directories
+    multi_tiff_pixel_size (int): size of images to chop to
+    pixel_size (float): pixel size in m
+    NA (float): NA of objective used to generate data
+    n_samples_forthresh (int): number of randomly chosen tiffs to use
+                    to determine thresholds for overall sample set
+    percentile (float): percentile of thresholds to use for overall data
+    giveNN (boolean): If true, also calculates Nearest Neighbors.
+                        Default False, as this is quite slow.
+    save_figs (boolean): If True, saves figures showing the segmentation
+                        for each image. Useful as a "sanity check"
+"""
+
+DAB_A.chop_and_analyse_svs(
+    overall_directory,
+    imtype=imtype,
+    multi_tiff_pixel_size=multi_tiff_pixel_size,
+    pixel_size=pixel_size,
+    NA=NA,
+    n_samples_forthresh=n_samples_forthresh,
+    percentile=percentile,
+    giveNN=giveNN,
+    save_figs=save_figs,
+)
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