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Bridging ImmunoGenomic Data Analysis Workflow Gaps (BIGDAWG): An integrated case-control analysis pipeline.

Derek J Pappas1, Wesley Marin2,3, Jill A Hollenbach2

  • 1Center for Genetics, Children's Hospital & Research Center Oakland, Oakland, CA.

Human Immunology
|December 29, 2015
PubMed
Summary

Bridging ImmunoGenomic Data-Analysis Workflow Gaps (BIGDAWG) standardizes analysis for complex HLA and KIR genetic data. This pipeline streamlines case-control studies, providing accurate statistical insights for immunogenetics research.

Keywords:
Amino-acid analysisBIGDAWGCase-control analysisHLA KIR data analysisHaplotype analysisHardy–Weinberg testingR packageWeb app

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Area of Science:

  • Immunogenetics
  • Bioinformatics
  • Computational Biology

Background:

  • Analysis of highly polymorphic genetic systems like HLA and KIR presents challenges for standard bioinformatics tools.
  • Existing methods often require error-prone data reformatting between different analysis programs.

Purpose of the Study:

  • To introduce Bridging ImmunoGenomic Data-Analysis Workflow Gaps (BIGDAWG), an integrated pipeline for standardized analysis of highly polymorphic genetic data.
  • To streamline and standardize data analysis for case-control studies involving HLA and KIR genetic systems.

Main Methods:

  • BIGDAWG performs Hardy-Weinberg equilibrium tests, allele frequency calculations, and allele binning for chi-squared tests.
  • It calculates odds ratios, confidence intervals, and p-values for alleles and user-specified haplotypes.
  • Amino-acid level analyses are performed for HLA loci, with automated figure and table generation.

Main Results:

  • BIGDAWG successfully integrates and standardizes the analysis of complex immunogenetic data.
  • The pipeline reduces errors associated with data reformatting between multiple software.
  • It provides comprehensive statistical outputs including allele and haplotype frequencies, and association test results.

Conclusions:

  • BIGDAWG offers a robust, standardized solution for analyzing highly polymorphic genetic data in case-control studies.
  • The tool facilitates more efficient and accurate immunogenetic research by integrating diverse analytical steps.
  • BIGDAWG is available as an R package and a web application, promoting accessibility.