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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"> | ||
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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) | ||
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### Supported Analyses | ||
<img src="https://github.com/user-attachments/assets/136c5ec4-5093-4129-a41b-233945e54198" width="250"/> | ||
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Initial supported analyses will include the mature genomics/bioinformatics pipelines developed within Breeding Insight, with additional analyses continuing to be added. | ||
</div> | ||
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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. | ||
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### Running the BIG app | ||
## Key Features | ||
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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. | ||
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Online preview: | ||
https://big-demo.shinyapps.io/bigapp/ | ||
## User Interface | ||
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**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> | ||
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**Online (in progress)** | ||
## Getting Started | ||
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## 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) | ||
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The BIG app relies on both custom scripts and previously developed R packages cited below: | ||
### Online Preview | ||
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* [R](): version 4.2.2 | ||
Try out a live demo of BIGapp here: [BIGapp Demo](https://big-demo.shinyapps.io/bigapp/) | ||
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#### R packages | ||
### Local Installation | ||
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* 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. | ||
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* 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) | ||
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* 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! | ||
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* 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 | ||
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* 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) | ||
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BIGapp leverages a powerful suite of R packages: | ||
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## Funding Sources | ||
Breeding Insight is funded by USDA through Cornell University. | ||
### Core R Packages | ||
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- **R (>= 4.2.2)** | ||
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### Shiny Framework | ||
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- [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. | ||
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### Genetic Analysis | ||
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- [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.” |