From ff40d6a7d0767675d04421281f7e510f11a2c0a1 Mon Sep 17 00:00:00 2001 From: Sean Davis Date: Thu, 16 May 2019 20:21:43 -0400 Subject: [PATCH] add Thies lab tutorial --- README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/README.md b/README.md index fe892fe..b1a7305 100644 --- a/README.md +++ b/README.md @@ -225,6 +225,7 @@ List of software packages (and the people developing these methods) for single-c - [Gilad Lab Single Cell Data Exploration](http://jdblischak.github.io/singleCellSeq/analysis/) - R-based exploration of single cell sequence data. Lots of experimentation. - [Harvard STEM Cell Institute Single Cell Workshop 2015](http://hms-dbmi.github.io/scw/) - workshop on common computational analysis techniques for scRNA-seq data from differential expression to subpopulation identification and network analysis. [See course description for more information](http://scholar.harvard.edu/jeanfan/classes/single-cell-workshop-2015) - [Hemberg Lab scRNA-seq course materials](http://hemberg-lab.github.io/scRNA.seq.course/index.html) +- [Theis Lab Single Cell Tutorial](https://github.com/theislab/single-cell-tutorial) - The main part of this repository is a case study where the best-practices established in the manuscript are applied to a mouse intestinal epithelium regions dataset from Haber et al., Nature 551 (2018) available from the GEO under GSE92332. - [Using Seurat (v1.2) for unsupervised clustering and biomarker discovery](http://www.satijalab.org/seurat/get_started_v1_2.html) - 301 single cells across diverse tissues from (Pollen et al., Nature Biotechnology, 2014). Original tutorial using Seurat 1.2 - [Using Seurat (v1.2) for spatial inference in single-cell data](http://www.satijalab.org/seurat/get_started_v1_2.html) - 851 single cells from Zebrafish embryogenesis (Satija*, Farrell* et al., Nature Biotechnology, 2015). Original tutorial using Seurat 1.2 - [Seurat (v3.0) - Guided Clustering Tutorial](https://satijalab.org/seurat/v3.0/immune_alignment.html) - new tutorial using Seurat 3.0