This is quick end-to-end tutorial on processing RNA Transcriptomics data presented here: https://themissingsemester.substack.com/p/the-missing-semester-rna-transcriptomics

A big thank you to Aneesa Valentine for putting together this tutorial :)

File organization

• README.md (this file): detailed explanation and presentation of process
• rna-transcript-eda.ipynb: full analysis in jupyter notebook using python

Why scRNA-seq?

Single cell RNA sequencing (scRNA-seq) is often used to identify individual cell population in a hetereogenous sample (like tissue or mix of cell lines).

As sequencing technologies become more accessible, interpreting the data is an important skill even for bench scientists.

Process

Install libraries needed

• scanpy: analyzing single-cell gene expression data
• matplotlib.pyplot: data visualization
• igraph: network analysis and visualization
• leidenalg: "facilitatoes community detection of networks", builds off of igraph
• numpy: array-processing

1. install/import all libraries mentioned in #Install libraries needed
2. Note: Might need to import ipywidgets as widgets if you get an javascript error