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The BIG app is a user-friendly R Shiny app to analyze genomic data without needing to use command-line tools and works across different species ploidy.

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(B)reeding (I)nsight (G)enomics app (BIGapp)

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.

Key Features

  • 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.

User Interface

BIGapp Screenshot
BIGapp's intuitive interface makes genomic data analysis accessible to everyone.

Getting Started

Tutorials

New to BIGapp? Check out our comprehensive tutorial to guide you through the process: BIGapp Tutorials

Online Preview

Try out a live demo of BIGapp here: BIGapp Demo

Local Installation

  1. Install R: Download and install the latest version of R from CRAN.
  2. Open Terminal (macOS/Linux) or R Console (Windows).
  3. Install and Run:
    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.

Online Deployment (Coming Soon)

BIGapp will be deployed on USDA SciNet for convenient online access. Stay tuned for updates!

Dependencies

BIGapp leverages a powerful suite of R packages:

Core R Packages

  • R (>= 4.2.2)

Shiny Framework

  • shiny: Web application framework.
  • shinyWidgets: Custom input widgets.
  • shinyalert: Create elegant pop-up messages.
  • shinyjs: Enhance Shiny apps with JavaScript actions.
  • shinydisconnect: Handle user disconnections gracefully.
  • shinycssloaders: Add CSS loaders for visual feedback.
  • bs4Dash: Bootstrap 4 dashboard components.
  • DT: Display data tables with interactive features.
  • config: Manage environment-specific configurations.

Genetic Analysis

  • updog: Genotype polyploid individuals.
  • GWASpoly: Conduct GWAS in polyploids.
  • AGHmatrix: Compute genomic relationship matrices.
  • rrBLUP: Perform genomic prediction.
  • BIGr: Breeding Insight's core genomic analysis functions.
  • adegenet: Explore and analyze genetic data.
  • vcfR: Manipulate and analyze VCF files.

Data Manipulation

  • dplyr: Data manipulation tools.
  • tidyr: Tidy your data.
  • purrr: Functional programming toolkit.
  • stringr: String manipulation.
  • future: Unified parallel and distributed processing.
  • tibble: Modern data frame alternative.

Statistical Analysis

  • factoextra: Extract and visualize multivariate analyses.
  • MASS: Statistical functions and datasets.
  • Matrix: Sparse and dense matrix operations.
  • matrixcalc: Matrix calculus functions.

Visualization

  • ggplot2: Create elegant data visualizations.
  • scales: Graphical scaling methods.
  • RColorBrewer: Color palettes for thematic maps.
  • plotly: Create interactive web graphics.

Funding

BIGapp development is supported by Breeding Insight, a USDA-funded initiative based at Cornell University.

Citation

If you use BIGapp in your research, please cite:

Sandercock, A.M., Peel, M.D., Taniguti, C., Chinchilla-Vargas, J., Chen, S., Sapkota, M., Lin, M., Zhao, D., Beil, C.T., Sheehan, M.J. (2024). BIGapp: A User-Friendly Genomic Tool Kit Identified Quantitative Trait Loci for Creeping Rootedness in Alfalfa (Medicago sativa L.). Manuscript in preparation.

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The BIG app is a user-friendly R Shiny app to analyze genomic data without needing to use command-line tools and works across different species ploidy.

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