Changes in version 0.99.8                        

                       Changes in version 0.99.7                        

                       Changes in version 0.99.6                        

                       Changes in version 0.99.5                        

  - Added read_vista_counts(), read_vista_metadata(), and
    match_vista_inputs() to standardize common RNA-seq input formats
    without changing the existing create_vista() API.
  - Added derive_vista_metadata() to bootstrap starter sample metadata
    from count-derived sample names using split- or regex-based parsing.
  - Added lightweight import support for plain count tables,
    featureCounts, STAR gene counts, HTSeq-count, tximport-like inputs,
    and RSEM gene result files.

                       Changes in version 0.99.4                        

                       Changes in version 0.99.3                        

                       Changes in version 0.99.2                        

                       Changes in version 0.99.1                        

  - example_vista() now uses a precomputed default object to reduce
    example, test, and package-check runtime while preserving the
    existing API.

                       Changes in version 0.99.0                        

Submitted to Bioconductor 2026-02-11

Overview

VISTA (Visualization Toolkit for Transcriptomic Analysis) provides a
unified S4-based framework for differential expression analysis of
RNA-seq data, wrapping DESeq2 and edgeR workflows with consistent
metadata management and rich visualization capabilities.

Key Features

Core Infrastructure

  - S4 VISTA class extending SummarizedExperiment for standardized data
    management
  - Unified differential expression workflow supporting DESeq2 and edgeR
    backends
  - Consistent metadata structure for comparisons, cutoffs, and group
    information
  - Flexible color palette system for visualizations

Visualization Suite (28+ functions)

  - Dimension reduction: PCA, MDS plots with customizable aesthetics
  - DE results: Volcano plots, MA plots, DEG count barplots
  - Expression: Barplots, boxplots, violin plots, density plots,
    joyplots, heatmaps
  - Comparisons: Venn diagrams, alluvial plots, correlation heatmaps,
    pairwise plots
  - Fold-change: Scatter plots, barplots, matrix visualizations,
    chromosome plots

Functional Analysis

  - MSigDB enrichment with flexible ID mapping (SYMBOL, ENSEMBL,
    ENTREZID)
  - GO enrichment analysis (BP, MF, CC ontologies)
  - KEGG pathway enrichment
  - GSEA support with customizable gene sets
  - Integrated visualization functions for enrichment results

Optional Features

  - Cell-type deconvolution via xCell2 integration
  - Automated report generation with Quarto
  - Accessor functions for all metadata components

Implementation Details

  - Comprehensive input validation and edge case handling
  - Extensive test suite (>70% coverage)
  - Complete roxygen2 documentation with runnable examples
  - BiocStyle vignettes demonstrating complete workflows
  - Proper namespace management and import declarations

Bug Fixes

  - Fixed contradictory roxygen documentation markers in internal
    utilities
  - Added missing @importFrom declarations across all modules
  - Improved error messages for invalid inputs
  - Enhanced edge case handling in visualization functions
  - Heatmap utilities now validate non-character genes input explicitly,
    support minimal-call defaults, and allow custom colours for
    multi-column annotations
  - DEG count pie/donut plots now optionally include non-DE genes as an
    "Other" slice and support configurable label text colour
  - get_genes_by_regulation() now supports top-gene ranking by
    abs(log2fc) and optional annotated table output
  - PCA/MDS/UMAP plots now accept the standardized use_group_colors
    argument while keeping use_vista_colors as a deprecated
    compatibility alias