iSEE: Interactive SummarizedExperiment Explorer

Abstract

Data exploration is critical to the comprehension of large biological data sets generated by high-throughput assays such as sequencing. However, most existing tools for interactive visualisation are limited to specific assays or analyses. Here, we present the iSEE (Interactive SummarizedExperiment Explorer) software package, which provides a general visual interface for exploring data in a SummarizedExperiment object. iSEE is directly compatible with many existing R/Bioconductor packages for analysing high-throughput biological data, and provides useful features such as simultaneous examination of (meta)data and analysis results, dynamic linking between plots and code tracking for reproducibility. We demonstrate the utility and flexibility of iSEE by applying it to explore a range of real transcriptomics and proteomics data sets.

Cited by papers we hold 6

• An atlas of cells in the human tonsil · 2024
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• SpatialExperiment: infrastructure for spatially-resolved transcriptomics data in R using Bioconductor · 2022
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• TreeSummarizedExperiment: a S4 class for data with hierarchical structure [version 1; peer review: 2 approved, 1 approved with reservations] · 2020
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• muscat detects subpopulation-specific state transitions from multi-sample multi-condition single-cell transcriptomics data · 2020
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• diffcyt: Differential discovery in high-dimensional cytometry via high-resolution clustering · 2019
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• Current best practices in single‐cell RNA‐seq analysis: a tutorial · 2019
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