Single Cell Analysis Toolbox

This repository contains data and notebooks for the single-cell session in the 2022 EMBL-EBI T-cell bioinformatics course

Objectives

The goal of these two sessions will be to introduce basic concepts for exploratory analysis of single-cell RNA and paired TCR sequencing data.

Data

We will use a dataset from the HCA Tissue Immune Cell Atlas containing human T cells across a range of lymphoid and non-lymphoid tissues. This will allow us to cover a broad spectrum of T cell types.

• scRNA-seq data available in the data folder of this repo and at Tissue Immune Cell Atlas

• scVDJ-seq data request access to TCR contigs in GDrive

notebooks

T-cell-bioinformatics-course_scRNAseq.ipynb - workflow to perform QC, integration and annotation of single-cell gene expression (GEX)

T-cell-bioinformatics-course_scTCRseq.ipynb - workflow to integrate VDJ and GEX data, determine clonotypes and repertoire sharing

Python_intro

Python packages

pip3 install

pandas numpy scipy matplotlib seaborn

Python object creation

dict = dict(zip(keys, values))

df = pd.DataFrame()

list = []

AnnData https://anndata.readthedocs.io/en/latest/

Reading in and writing out the data

pd.read_csv() .to_csv()

Investigating objects

type()

Dataframes: df.columns df.shape df['column'].unique() df['column'].nunique() df.head(2) df.tail(2) df['column.value_counts

Python courses

https://www.w3schools.com/python/python_intro.asp

https://www.bioinformatics.babraham.ac.uk/training.html

https://swcarpentry.github.io/python-novice-inflammation/

http://swcarpentry.github.io/python-novice-gapminder/