tutorials

single cell sequencing general tutorials

This tutorial will give you a general introduction into single-cell sequencing analysis using scanpy and besca. It is divided into three seperate notebooks that should be looked at in consecutive order (they build up on results from the previous notebooks).

Part 1: data processing

Part 2: celltype annotation

Part 3: batch correction

After looking at the introductory tutorial you can download the hands-on tutorial yourself from scRNAseq_tutorial.ipynb (please save the link as a .ipynb file) and compare with the results published here.

single cell auto_annot tutorial for cell type annotation

We also provide a tutorial for the auto_annot package, which allows to automatically annotate cell types using supervised machine learning, you can download it from here (please save the link as a .ipynb file) and compare with the results published <tutorials/auto_annot_tutorial>.

Bescape: cell deconvolution tutorial

Bescape (BESCA proportion estimator) is a deconvolution module. It utilises single-cell annotations coming from the BESCA workflow to build a Gene Expression Profile (GEP). This GEP is used as a basis vector to deconvolute bulk RNA samples i.e. predict cell type proportions within a sample.

Deconvolution tutorial: Bescape

Some deconvolution methods provided by Bescape are written in R. Thus, we need to convert the AnnData objects to R ExpressionSet objects. This has been semi-automated :

adata_to_eset tutorial: here