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AlleloBin: A Shiny Application for Allele Binning in Microsatellite Markers

AlleloBin is an R package designed to automate the conversion of imprecise fragment sizes from automated DNA sequencers into representative, discrete allele sizes. It implements and extends the least-squares minimization algorithm developed by Idury & Cardon (1997) to eliminate time-consuming manual intervention in high-throughput genotyping workflows.

👥 Authors & Citation

• VP Prasanth, S Chandra, DA Hoisington, B Jayashree
• International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India.
• Contact/E-mail: prasanth.stat@gmail.com

If you use this software, please cite: > Idury, R. M., & Cardon, L. R. (1997). A least-squares algorithm for a semi-automated allele sizing system. Genome Research, 7(11), 1104-1109.

✨ Key Features

• Automated Binning: Rapidly processes large-scale genotyping datasets using an objective least-squares algorithm.
• Ploidy Flexibility: Extends the original algorithm to support multi-ploidy levels (not just diploids).
• Quality Control: Generates useful summary statistics, calculates a distinct quality index for each marker, and checks for allelic drift.
• Interactive Visualization: Produces clear histograms overlaying observed data with inferred allele classes for easy visual inspection.
• User-Friendly Interface: Includes an interactive R Shiny application for researchers who prefer a graphical interface over command-line code.

🛠️ Installation

You can install the development version of AlleloBin directly from GitHub using the devtools package:

# Install devtools if you haven't already
if (!requireNamespace("devtools", quietly = TRUE)) {
  install.packages("devtools")
}

# Install AlleloBin
devtools::install_github("vpprasanth/AlleloBin")

🚀 Quick Start

Command Line Usage

library(AlleloBin)

# 1. Load your raw fragment size genotyping data
my_data <- read.table(system.file("extdata", "data.txt", package = "AlleloBin"), header = FALSE)

# 2. Load the corresponding marker configuration data (repeat lengths, etc.)
marker_info <- read.table(system.file("extdata", "repeat_length.txt", package = "AlleloBin"), header = FALSE)

# 3. Extract the repeat lengths vector from the repeat_length file
repeat_lens <- marker_info$V1 

# 4. Run the binning process
results <- allele_binning(data = my_data, repeat_lengths = repeat_lens, ploidy = 2)

# Save results to Excel
save_results(results, "AlleloBin_Output.xlsx")

Launch the Shiny Web Interface

If you prefer a graphical layout to upload your files and look at histograms, simply launch the built-in app:

library(AlleloBin)
AlleloBin()

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.