# VISTA 0.99.8

# VISTA 0.99.7

# VISTA 0.99.6

# VISTA 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.

# VISTA 0.99.4

# VISTA 0.99.3

# VISTA 0.99.2

# VISTA 0.99.1

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

# VISTA 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

---
