SuperResNET supports loading SMLM point cloud data from various microscopes (e.g., dSTORM, PALM, DNA-PAINT) with different file formats (e.g., non-text binary, text, and ASCII formats). See the microscopy data formats that SuperResNET supports in the video
Note 1. SuperResNET will inform you when trying to load unsupported file format. You might need to prepare your file into one of the supported microscopy formats (e.g., .3dlp, .bin, .ascii) or generate a file with the localization coordinates in X, Y, Z and save it as one of the supported general formats (e.g., .txt, .xyz). You can save the file with or without header information. SuperResNET can load both types of files
Please contact Ismail Khater if you have trouble loading your data
General Notes When using SuperResNET
SuperResNET can be used to process 2D data by including a zero-valued, the third Z coordinate for each (X,Y) 2D coordinate. SuperResNET can be used to process/visualize the 2D data. However, some of the features will be calculated to zeros in the Blob Features Module/Tab (e.g., volume) as these features are designed for 3D data only.
SuperResNET is installed on personal computer to process the whole field of view (FOV) or a cropped region of interest (ROI). For big SMLM data with a relatively large number of localizations (e.g. > 1millions from a large field of views), then we recommend using a machine with large memory (e.g., 32GB, 64GB, or even larger). SuperResNET can be used to crop ROIs to improve runtimes.
SuperResNET is a relatively fast software. However, when segmenting big-data using the mean-shift algorithm [1, 2], it might take minutes to hours depending on the size of the data and the computer specifications (CPU speed and RAM size). SuperResNET also supports the use of the DBSCAN  algorithm to segment biological structures (i.e., clusters) of various shapes.
See the step-by-step video guide for using SuperResNET or read the details below
SuperResNET GUI Tabs
Load Data Tab
Merge & Network Analysis Tab
Blob Features Tab
Blob Groups Tab
Group Features Tab
Visualizing Individual Features
Visualizing Feature Pairs
Individual Blobs Tab
Exploring blob from class 1
Exploring blob from class 2
Exploring blob from class 3