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HAPPE: A Tool for Population Haplotype Analysis and Visualization in Editable Excel Tables.

Cong Feng1, Xingwei Wang1,2,3, Shishi Wu1,2,3

  • 1Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences (CAAS), Shenzhen, China.

Frontiers in Plant Science
|July 18, 2022
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Summary

Haplotype analysis is crucial for population genomics. The new HAPPE tool visualizes haplotype patterns and genotypes alongside genomic data, aiding in variant detection and user-friendly data exploration.

Keywords:
ExcelSNPshaplotypephylogenetic clusteringvisualization

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Haplotype identification and visualization are essential for population genomics.
  • Existing tools struggle to display complex haplotype patterns and single nucleotide polymorphism (SNP) genotypes within large genomic datasets.

Purpose of the Study:

  • To introduce HAPPE, a novel tool for characterizing and visualizing genotypes and haplotypes in a phylogenetic context.
  • To provide a user-friendly method for displaying detailed genomic information for non-programmers.

Main Methods:

  • Utilizes agglomerative hierarchical clustering to analyze haplotype data.
  • Generates visualizations in Excel tables, coloring cells and borders to represent data.
  • Supports parallel display of phylogenetic trees, GWAS P-values, gene/SNP information, and sequencing depth.

Main Results:

  • HAPPE effectively visualizes haplotype patterns and genotypes, integrating diverse genomic data.
  • The tool facilitates the detection of insertions/deletions and copy number variations through informative plots.
  • Editable Excel-based plots offer an accessible interface for data interpretation.

Conclusions:

  • HAPPE offers a powerful and user-friendly solution for haplotype characterization and visualization in population genomics.
  • The tool's integration capabilities and intuitive output enhance the analysis of complex genomic data.
  • HAPPE is available as a Python pipeline, promoting accessibility for researchers.