Abstract
Data organized into hierarchical structures (e.g., phylogenies or cell types) arises in several biological fields. It is therefore of interest to have data containers that store the hierarchical structure together with the biological profile data, and provide functions to easily access or manipulate data at different resolutions. Here, we present TreeSummarizedExperiment, a R/S4 class that extends the commonly used SingleCellExperiment class by incorporating tree representations of rows and/or columns (represented by objects of the phylo class). It follows the convention of the SummarizedExperiment class, while providing links between the assays and the nodes of a tree to allow data manipulation at arbitrary levels of the tree. The package is designed to be extensible, allowing new functions on the tree (phylo) to be contributed. As the work is based on the SingleCellExperiment class and the phylo class, both of which are popular classes used in many R packages, it is expected to be able to interact seamlessly with many other tools.
Highlights
Biological data arranged into a hierarchy occurs in several fields
A notable example is in microbial survey studies, where the microbiome is profiled with amplicon sequencing or whole genome shotgun sequencing, and microbial taxa are organized as a tree according to their similarities in the genomic sequence or the evolutionary history
The former supports the information pertaining to the hierarchical structure that is available as the phylo class, and the latter is derived from the SummarizedExperiment class, which is widely used as a standardized container across many Bioconductor packages
Summary
Shila Ghazanfar , University of Cambridge, Cambridge, UK. Any reports and responses or comments on the article can be found at the end of the article. TreeSummarizedExperiment (TSE) allows rowTree() and colTree() to work as both setters and getters, provides a new slot referenceSeq() to store sequence information, and replaces aggValue with aggTSE to provide more flexible data aggregation. An example analysis of CyTOF data is added as a new use case of TreeSummarizedExperiment. This necessarily added new commands and text to describe new features of TSE. Any further responses from the reviewers can be found at the end of the article
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