---
title: "Introduction to ClinicalVariantR"
author:
  - name: Safa Rafique
    email: safa.sandhu@gmail.com
    orcid: 0000-0003-2646-8106
  - name: Naeem Mahmood
    email: naeem.sbb@pu.edu.pk
  - name: Muhammad Farooq Sabar
    email: farooq.sbb@pu.edu.pk
package: ClinicalVariantR
output:
  BiocStyle::html_document:
    toc: true
    toc_depth: 2
vignette: >
  %\VignetteIndexEntry{Introduction to ClinicalVariantR}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(
    collapse = TRUE,
    comment = "#>",
    eval = TRUE,
    message = FALSE,
    warning = FALSE
)
```

# Overview

**ClinicalVariantR** is an R / Bioconductor software package that classifies germline
sequence variants under the ACMG/AMP 2015 framework from pre-annotated VCF
files (VEP CSQ, SnpEff ANN, or ANNOVAR-style INFO fields).

The package exposes an interactive Shiny application with three workflows:

| Workflow | Inputs | Purpose |
|----------|--------|---------|
| Group A (full clinical) | VCF + clinical log + pedigree | Automated criteria plus curator toggles |
| Group B (rapid) | VCF only | High-throughput automated classification |
| Group C (gene panel) | VCF + gene list | Panel-restricted automated classification |

# Installation

```r
if (!requireNamespace("BiocManager", quietly = TRUE)) {
    install.packages("BiocManager")
}
BiocManager::install("ClinicalVariantR")
```

Until the package is accepted on Bioconductor, install from GitHub:

```r
# install.packages("remotes")
remotes::install_github("safarafique/ClinicalVariantR")
```

# Launching the Shiny app

Following Bioconductor Shiny guidelines, package functions **return** a Shiny
app object; the user launches it:

```{r launch}
if (requireNamespace("ClinicalVariantR", quietly = TRUE)) {
    stopifnot(is.function(ClinicalVariantR::ClinicalVariantR))
}
# To launch interactively:
# shiny::runApp(ClinicalVariantR())
```

`ClinicalVariantRApp()` is an alias of `ClinicalVariantR()`.

For a full walkthrough of launching the app, choosing sample VCFs, Group A/B/C
UI checks, and command-line tests, see the companion vignette
**Running and testing ClinicalVariantR** (`vignettes/ClinicalVariantR-run-and-test.Rmd`).

# Input requirements

- **VCF** (`.vcf` or `.vcf.gz`) with VEP `CSQ`, SnpEff `ANN`, or ANNOVAR-style
  annotation for consequence, gene symbol, transcript, population AF, ClinVar,
  and in silico scores when available.
- Optional **clinical log** and **pedigree** CSV files for Group A.
- Optional **gene symbol list** for Group C.

Default reference tables under `inst/extdata/reference/` are placeholders;
population and prediction evidence primarily use annotation embedded in the
VCF unless curated references are installed (see package `README`).

# Scope and limitations

ClinicalVariantR targets **germline SNV and small-indel** interpretation. It does not
classify somatic variants, structural variants, CNVs, or mitochondrial genomes.
Several ACMG criteria require external data (functional assays, phasing,
matched pathogenic variants) and are registered as manual or not automated.

See the package `NEWS` file and GitHub README for version-specific criterion
coverage and validation notes.

# Session info

```{r sessionInfo}
sessionInfo()
```