QC & preprocessing
As a first step after importing the data into TreeSummarizedExperiment, one should explore the data and perform quality control (QC). This is important because data quality affects the final results, and failing to assess it accurately can lead to erroneous interpretations. QC and exploration are discussed in 8 Exploration & quality control.
Based on the QC results, researchers usually apply sample and feature filtering to improve the robustness of the analysis. To focus on a specific taxonomic rank, data agglomeration is commonly performed. Filtering and agglomeration are discussed in detail in 9 Subsetting and 10 Agglomeration.
Data transformations, covered in 11 Transformation, are applied after filtering. For more information on preprocessing, you can refer to Zhou et al. (2023), for instance.