{ "cells": [ { "cell_type": "markdown", "id": "d008e5a2-2953-4850-94bd-53dea95ae0ad", "metadata": {}, "source": [ "# Celltype auto annotation with SCSA\n", "Single-cell transcriptomics allows the analysis of thousands of cells in a single experiment and the identification of novel cell types, states and dynamics in a variety of tissues and organisms. Standard experimental protocols and analytical workflows have been developed to create single-cell transcriptomic maps from tissues. \n", "\n", "This tutorial focuses on how to interpret this data to identify cell types, states, and other biologically relevant patterns with the goal of creating annotated cell maps.\n", "\n", "Paper: [SCSA: A Cell Type Annotation Tool for Single-Cell RNA-seq Data](https://doi.org/10.3389/fgene.2020.00490)\n", "\n", "Code: https://github.com/bioinfo-ibms-pumc/SCSA\n", "\n", "Colab_Reproducibility:https://colab.research.google.com/drive/1BC6hPS0CyBhNu0BYk8evu57-ua1bAS0T?usp=sharing\n", "\n", "
Note
\n", "\n", " The annotation with SCSA can't be used in rare celltype annotations\n", "
\n", "Note
\n", "\n", " The annotation with SCSA need to download the database at first. It can be downloaded automatically. But sometimes you will have problems with network errors.\n", "
\n", "