QC, pre-processing and normalisation

Trainer: Iris Diana Yu

Overview: In this session, we will cover essential techniques for preparing data for analysis. We will begin with Quality Control (QC) to assess and ensure the integrity and reliability of our data, identifying and addressing any errors or inconsistencies. Next, we will explore pre-processing steps, which involve cleaning and organising the data to make it suitable for analysis. Finally, we will discuss normalisation methods to standardise data values, making them comparable and enhancing the accuracy of subsequent analyses.

Materials:

• Presentation slides

Practical materials:

• GitHub repository