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Data Preprocessing

The preprocessing is the most important part of a single cell analysis because you can skew your result if you filter too much or too little and you must really understand what's going on these steps.

The preprocesing is composed of:

  • Filtering of low quality barcodes
  • Barcode normalization
  • Selection of most variable features

Please go read the preprocessing pages to learn more about it.

Do it yourself!

Now it's your time to shine ! We are going to put into pratice what we have just seen. By using a more complicated use case, you are going to reproduce the whole scRNAseq analysis with Seurat.

Dataset test

The dataset for this analysis will be single cell RNAseq from zebrafish embryos from Metikala et al. You need to continue your RMD/QMD from last week.

Render your RMD/QMD

To complete this week you'll need to :

  • 1. Filtering the low quality barcodes and explain each cutoff
  • 2. Normalize the data
  • 3. Identify the most variable genes

IMPORTANT

Please note you must be explicative in your cutoff choices and detailled each step of your thoughts. In general, try to explain in your own words, each step of your analysis !

Add your RMD/QMD in your Trello card.

Thank you for your attention and see you next week 👏 👏 👏