Cleaning Up the Noise: Data Preprocessing & Normalization

The Speaker

Katrien Quintelier - VIB-UGent Center for Inflammation Research | Data Mining and Modeling for Biomedicine

Katrien Quintelier is a [doctoral / postdoctoral] researcher working in the group of Prof. Yvan Saeys at the VIB-UGent center for Inflammation Research in Belgium. Her research lies at the intersection of computational biology and immunology, with a strong focus on the analysis of high-dimensional cytometry and CITE-seq data. Since Katrien is working with clinical data, her main research focus is on the preprocessing of the data including quality control, batch effect detection and correction.
 

Summary

This webinar will provide a comprehensive overview of the preprocessing pipeline for cytometry data. We will cover the required and optional steps to obtain high-quality, preprocessed data that is ready for downstream analysis, including compensation, transformation and doublet removal. Particular focus will be given to quality control: addressing strategies at the per-file level to filter out low-quality events, as well as across files to identify and manage batch effects.

Learning Objectives:

After attending this webinar, participants will be able to:

1. Understand the different preprocessing steps
2. Be aware of the different levels of quality control
3. Understand how batch effect correction works

Who Should Attend:

Anyone interested in cytometry data analysis.

CMLE Credit: 1.0