{ "cells": [ { "cell_type": "markdown", "id": "7f7b47ec-1e48-4c6a-99cb-fb74d4c08840", "metadata": {}, "source": [ "# SpaSEG\n", "\n", "**SpaSEG**, an unsupervised convolutional neural network-based method towards multiple SRT analysis tasks by jointly learning transcriptional similarity between spots and their spatial dependence within tissue. **SpaSEG** adopts edge strength constraint to enable coherent spatial domains, and allows integrative SRT analysis by automatically aligning spatial domains across multiple adjacent sections. Moreover, **SpaSEG** can effectively detect spatial domain-specific gene expression patterns(SVG), and infer intercellular interactions and co-localizations[[Bai23]](https://www.biorxiv.org/content/10.1101/2022.11.16.516728v2.full)." ] }, { "cell_type": "markdown", "id": "3e475a32-c5a9-48d5-8bf0-3bbd3555f525", "metadata": {}, "source": [ "