From 77d0c2ad5a7e64d1c895c5534caa17cb72ea8eb8 Mon Sep 17 00:00:00 2001
From: Alexander Sandercock <39815775+alex-sandercock@users.noreply.github.com>
Date: Sat, 28 Dec 2024 10:35:04 -0500
Subject: [PATCH] Update README.md
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[![R-CMD-check](https://github.com/Breeding-Insight/BIGapp/workflows/R-CMD-check/badge.svg)](https://github.com/Breeding-Insight/BIGapp/actions)
-[![Development](https://img.shields.io/badge/development-active-blue.svg)](https://img.shields.io/badge/development-active-blue.svg)
-
+[![Development Status](https://img.shields.io/badge/development-active-blue.svg)](https://img.shields.io/badge/development-active-blue.svg)
+
-# (B)reeding (I)nsight (G)enomics app
+
-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
+
-Initial supported analyses will include the mature genomics/bioinformatics pipelines developed within Breeding Insight, with additional analyses continuing to be added.
+
-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
+
+
+
+ BIGapp's intuitive interface makes genomic data analysis accessible to everyone.
+
-**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.”