Changelog • STID

STID 0.0.0.9000

This is the first development release of STID, a spatial transcriptomics toolkit for infectious disease studies.

Introduced STID as a standardized and reproducible framework for analyzing infection-associated spatial transcriptomics data.
Established an infection-specific analysis workflow that leverages the Seurat ecosystem and incorporates Python-based modules where needed.
Supported spatial transcriptomics studies of infectious diseases caused by bacteria, viruses, and parasites.
Provided functionality for characterizing pathogen-infected and host-responsive niches, including their spatial structure, cellular composition, molecular functions, and host-pathogen interactions.

Added support for constructing and organizing infection-associated spatial transcriptomics data.
Added workflows for data conversion, preprocessing, annotation, and quality-controlled downstream analysis.
Added pathogen background correction to improve interpretation of pathogen-derived signals.
Added methods for detecting infection-associated spots from pathogen genes or pathogen-related gene sets.
Added methods for identifying infection-associated spatial niches.
Added single-sample analysis workflows for characterizing infection-associated niches within individual samples.
Added multi-sample and temporal analysis workflows for comparing infection-associated spatial patterns across samples or disease stages.
Added visualization, plotting, and utility functions to support interpretation of STID analysis results.

The following functions are representative examples of the current STID interface and do not constitute a complete list of available functions.

Added data conversion utilities, including h5ad2rds() and rds2h5ad().
Added preprocessing and annotation utilities, including Seurat_pipeline() and anno_SingleR().
Added pathogen background correction with CorrectBackground().
Added infection-associated spot detection utilities, including SpotDetect_Gene() and SpotDetect_Geneset().
Added infection-associated niche identification utilities, including NicheDetect_Lasso() and NicheDetect_STS().
Added single-sample analysis utilities, including CalSampComp() and CalSampDEGs().
Added multi-sample analysis utilities, including CalSampPathoTrack() and CalSampGeneTrend().

Added the package README with an overview, key features, installation instructions, quick start information, resources, and citation details.
Added online tutorials covering installation, data loading and preprocessing, pathogen background correction, infection-associated spot detection, infection-associated niche identification, single-sample analysis, and multi-sample analysis.
Added advanced documentation for the STID class, plotting functions, and utility functions.

Added the Gene_Geneset dataset for gene and gene set information used in STID workflows.
Added links to raw and processed datasets used in the associated study and tutorials.
Added links to the GitHub repository, tutorial website, archived study version, and reproducible analysis scripts.

Added GitHub-based installation via remotes::install_github("YulongQin/STID").
Added installation guidance for CRAN and Bioconductor mirror configuration.
Added recommendations for using an isolated R library path to improve reproducibility.
Added pre-installation notes for dependency management, source installation, binary packages, timeout configuration, and compilation settings.

STID is under active development.
Function names, APIs, tutorials, and analysis workflows may continue to evolve in future development versions.