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Copy file name to clipboardExpand all lines: posts/2025-01-15-introducing-tidyomics-ecosystem/index.qmd
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### tidyprint
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`tidyprint` offers a consistent, user-friendly print method for Bioconductor objects such as `SummarizedExperiment`, `SingleCellExperiment`, and others. It flattens complex S4 objects into tidy tibbles for straightforward inspection, summarization, and reporting—without modifying the underlying data. This approach makes it easy to explore and understand your data at a glance using familiar tidyverse conventions.
Single-cell experiments often contain millions of cells and dozens of matrices. `tidySingleCellExperiment` flattens this complexity so you can focus on the biology instead of the bookkeeping.
Spatial transcriptomics combines gene expression with tissue geography. `tidySpatialExperiment` brings the tidy philosophy to `SpatialExperiment` objects so you can transform, visualise and model spatial spots with the same verbs you already use for bulk and single-cell data.
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### tidybulk
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A tidy framework for modular transcriptomic data analysis, `tidybulk` streamlines bulk RNA-seq workflows by integrating differential expression, batch correction, and gene set enrichment into a consistent, pipe-friendly grammar. It enables users to perform complex analyses with simple, readable code, leveraging tidyverse principles for reproducibility and clarity.
A tidy interface for statistical null range generation and overlap analysis in genomics. `nullranges` enables users to create matched sets of genomic ranges for robust enrichment testing, supporting reproducible and flexible workflows for tasks such as permutation-based significance assessment and background modeling.
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