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# (B)reeding (I)nsight (G)enomics app <img src="https://github.com/user-attachments/assets/136c5ec4-5093-4129-a41b-233945e54198" align="right" width="250"/>
<div align="center">

The BIGapp is a user-friendly tool for processing low to mid-density genotyping data for diploid and polyploid species. This R shiny app provides a web-based user friendly way for users to analyze genomic data without needing to use command-line tools. Additional analysis will be added, with the initial focus on a core set of features for supporting breeding decisions.
# (B)reeding (I)nsight (G)enomics app (BIGapp)

### Supported Analyses
<img src="https://github.com/user-attachments/assets/136c5ec4-5093-4129-a41b-233945e54198" width="250"/>

Initial supported analyses will include the mature genomics/bioinformatics pipelines developed within Breeding Insight, with additional analyses continuing to be added.
</div>

Supported:
- Genotype processing
- Dosage call from read counts
- SNP filtering
- Sample filtering
- Summary metrics
- SNP Polymorphism Information Content
- SNP Minor Allele Frequency
- Sample Observed Heterozygosity
- Population Structure
- PCA
- DAPC
- GWAS
- GWASpoly
- GS
- Estimate Model Prediction Accuracy
- Predict Phenotype Values and EBVs for Samples
BIGapp is a user-friendly web application built with R and Shiny, designed to simplify the processing of low to mid-density genotyping data for both diploid and polyploid species. It provides a powerful and intuitive interface for researchers and breeders to analyze genomic data without requiring command-line expertise.

### Running the BIG app
## Key Features

Tutorial available:
https://scribehow.com/page/BIGapp_Tutorials__FdLsY9ZxQsi6kgT9p-U2Zg
- **Web-Based Interface:** Access BIGapp through your web browser, eliminating the need for complex software installations.
- **Genotype Processing:**
- Call genotypes from read counts.
- Filter SNPs based on various criteria.
- Filter samples to ensure data quality.
- **Summary Statistics:**
- Calculate SNP Polymorphism Information Content (PIC).
- Determine SNP Minor Allele Frequency (MAF).
- Compute Sample Observed Heterozygosity.
- **Population Structure Analysis:**
- Perform Principal Component Analysis (PCA).
- Conduct Discriminant Analysis of Principal Components (DAPC).
- **Genome-Wide Association Studies (GWAS):**
- Utilize GWASpoly for robust association mapping.
- **Genomic Selection (GS):**
- Estimate model prediction accuracy.
- Predict phenotypic values and Estimated Breeding Values (EBVs) for your samples.
- **Expanding Functionality:** BIGapp is actively developed, with new analyses and features continuously being added.

Online preview:
https://big-demo.shinyapps.io/bigapp/
## User Interface

**Local computer**
1. Install R
2. Open Terminal (on mac)
3. To install and run development version of package:
(in terminal)
```
install.packages("devtools") #If not already installed
devtools::install_github("Breeding-Insight/BIGapp")
BIGapp::run_app()
```
4. View shiny app in browser
<p align="center">
<img src="https://github.com/user-attachments/assets/9a6984df-8116-403c-85c1-ba9600623940" alt="BIGapp Screenshot" width="800"/>
<br>
<em>BIGapp's intuitive interface makes genomic data analysis accessible to everyone.</em>
</p>

**Online (in progress)**
## Getting Started

## Third-party software
### Tutorials
New to BIGapp? Check out our comprehensive tutorial to guide you through the process: [BIGapp Tutorials](https://scribehow.com/page/BIGapp_Tutorials__FdLsY9ZxQsi6kgT9p-U2Zg)

The BIG app relies on both custom scripts and previously developed R packages cited below:
### Online Preview

* [R](): version 4.2.2
Try out a live demo of BIGapp here: [BIGapp Demo](https://big-demo.shinyapps.io/bigapp/)

#### R packages
### Local Installation

* Shiny tools: [shiny](https://cran.r-project.org/web/packages/shiny/index.html), [shinyWidgets](https://cran.r-project.org/web/packages/shinyWidgets/index.html), [shinyalert](https://cran.r-project.org/web/packages/shinyalert/index.html), [shinyjs](https://cran.r-project.org/web/packages/shinyjs/index.html), [shinydisconnect](https://cran.r-project.org/web/packages/shinydisconnect/index.html), [shinycssloaders](https://cran.r-project.org/web/packages/shinycssloaders/index.html), [bs4Dash](https://cran.r-project.org/web/packages/bs4Dash/index.html), [DT](https://cran.r-project.org/web/packages/DT/index.html), [config](https://cran.r-project.org/web/packages/config/index.html)
1. **Install R:** Download and install the latest version of R from [CRAN](https://cran.r-project.org/).
2. **Open Terminal (macOS/Linux) or R Console (Windows).**
3. **Install and Run:**
```R
if (!requireNamespace("devtools", quietly = TRUE))
install.packages("devtools")
devtools::install_github("Breeding-Insight/BIGapp")
BIGapp::run_app()
```
4. **Access in Browser:** The BIGapp interface will open in your default web browser.

* Genetic analysis: [updog](https://cran.r-project.org/web/packages/updog/index.html), [GWASpoly](https://github.com/jendelman/GWASpoly), [AGHmatrix](https://cran.r-project.org/web/packages/AGHmatrix/index.html), [rrBLUP](https://cran.r-project.org/web/packages/rrBLUP/index.html), [BIGr](https://github.com/Breeding-Insight/BIGr), [adegenet](https://cran.r-project.org/web/packages/adegenet/index.html), [vcfR](https://cran.r-project.org/web/packages/vcfR/index.html)
### Online Deployment (Coming Soon)

* Data manipulation optimization: [dplyr](https://cran.r-project.org/web/packages/dplyr/index.html), [tidyr](https://cran.r-project.org/web/packages/tidyr/index.html), [purrr](https://cran.r-project.org/web/packages/purrr/index.html), [stringr](https://cran.r-project.org/web/packages/stringr/index.html), [future](https://cran.r-project.org/web/packages/future/index.html), [tibble](https://cran.r-project.org/web/packages/tibble/vignettes/tibble.html)
BIGapp will be deployed on USDA SciNet for convenient online access. Stay tuned for updates!

* Statistical analysis: [factoextra](https://cran.r-project.org/web/packages/factoextra/index.html), [MASS](https://cran.r-project.org/web/packages/MASS/index.html), [Matrix](https://cran.r-project.org/web/packages/Matrix/index.html), [matrixcalc](https://cran.r-project.org/web/packages/matrixcalc/index.html)
## Dependencies

* Generate pretty graphics: [ggplot2](https://cran.r-project.org/web/packages/ggplot2/index.html), [scales](https://cran.r-project.org/web/packages/scales/index.html), [RColorBrewer](https://cran.r-project.org/web/packages/RColorBrewer/index.html), [plotly](https://cran.r-project.org/web/packages/plotly/index.html)

BIGapp leverages a powerful suite of R packages:

## Funding Sources
Breeding Insight is funded by USDA through Cornell University.
### Core R Packages

- **R (>= 4.2.2)**

### Shiny Framework

- [shiny](https://cran.r-project.org/web/packages/shiny/index.html): Web application framework.
- [shinyWidgets](https://cran.r-project.org/web/packages/shinyWidgets/index.html): Custom input widgets.
- [shinyalert](https://cran.r-project.org/web/packages/shinyalert/index.html): Create elegant pop-up messages.
- [shinyjs](https://cran.r-project.org/web/packages/shinyjs/index.html): Enhance Shiny apps with JavaScript actions.
- [shinydisconnect](https://cran.r-project.org/web/packages/shinydisconnect/index.html): Handle user disconnections gracefully.
- [shinycssloaders](https://cran.r-project.org/web/packages/shinycssloaders/index.html): Add CSS loaders for visual feedback.
- [bs4Dash](https://cran.r-project.org/web/packages/bs4Dash/index.html): Bootstrap 4 dashboard components.
- [DT](https://cran.r-project.org/web/packages/DT/index.html): Display data tables with interactive features.
- [config](https://cran.r-project.org/web/packages/config/index.html): Manage environment-specific configurations.

### Genetic Analysis

- [updog](https://cran.r-project.org/web/packages/updog/index.html): Genotype polyploid individuals.
- [GWASpoly](https://github.com/jendelman/GWASpoly): Conduct GWAS in polyploids.
- [AGHmatrix](https://cran.r-project.org/web/packages/AGHmatrix/index.html): Compute genomic relationship matrices.
- [rrBLUP](https://cran.r-project.org/web/packages/rrBLUP/index.html): Perform genomic prediction.
- [BIGr](https://github.com/Breeding-Insight/BIGr): Breeding Insight's core genomic analysis functions.
- [adegenet](https://cran.r-project.org/web/packages/adegenet/index.html): Explore and analyze genetic data.
- [vcfR](https://cran.r-project.org/web/packages/vcfR/index.html): Manipulate and analyze VCF files.
### Data Manipulation
- [dplyr](https://cran.r-project.org/web/packages/dplyr/index.html): Data manipulation tools.
- [tidyr](https://cran.r-project.org/web/packages/tidyr/index.html): Tidy your data.
- [purrr](https://cran.r-project.org/web/packages/purrr/index.html): Functional programming toolkit.
- [stringr](https://cran.r-project.org/web/packages/stringr/index.html): String manipulation.
- [future](https://cran.r-project.org/web/packages/future/index.html): Unified parallel and distributed processing.
- [tibble](https://cran.r-project.org/web/packages/tibble/vignettes/tibble.html): Modern data frame alternative.
### Statistical Analysis
- [factoextra](https://cran.r-project.org/web/packages/factoextra/index.html): Extract and visualize multivariate analyses.
- [MASS](https://cran.r-project.org/web/packages/MASS/index.html): Statistical functions and datasets.
- [Matrix](https://cran.r-project.org/web/packages/Matrix/index.html): Sparse and dense matrix operations.
- [matrixcalc](https://cran.r-project.org/web/packages/matrixcalc/index.html): Matrix calculus functions.
### Visualization
- [ggplot2](https://cran.r-project.org/web/packages/ggplot2/index.html): Create elegant data visualizations.
- [scales](https://cran.r-project.org/web/packages/scales/index.html): Graphical scaling methods.
- [RColorBrewer](https://cran.r-project.org/web/packages/RColorBrewer/index.html): Color palettes for thematic maps.
- [plotly](https://cran.r-project.org/web/packages/plotly/index.html): Create interactive web graphics.
## Funding
BIGapp development is supported by [Breeding Insight](https://www.breedinginsight.org/), a USDA-funded initiative based at Cornell University.
## Citation
If you use BIGapp in your research, please cite:
Sandercock, Alexander M., Cristiane Taniguti, Josue Chinchilla-Vargas, Shufen Chen, Manoj Sapkota, Meng Lin, Dongyan Zhao, and Breeding Insight Team. 2024. “BIGapp: Breeding Insight Genomics Shiny Application.”

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