add Thies lab tutorial

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