DRI-Based Evolutionary Biology Analysis Tutorials

Project Overview

Welcome to the DRI-Based Evolutionary Biology Analysis Tutorial! This tutorial series is designed to guide you through the essential computational tools and methods for analyzing genetic data in evolutionary biology, utilizing resources from Canada’s Digital Research Infrastructure (DRI). The aim of this project is to empower researchers, particularly those from equity-seeking groups to access and leverage high-performance computing and advanced bioinformatics tools to conduct comprehensive evolutionary analyses.

Tutorial Outline

  1. High-Throughput Sequencing Data Preprocessing
    Learn how to trim, align, sort, and deduplicate sequencing reads to ensure high-quality genomic analysis.
  2. SNP and INDEL Detection
    Learn how to identify single nucleotide polymorphisms (SNPs) and insertions/deletions (INDELs) in genomic data, fundamental for studying genetic variation within populations.
  3. Structural Variants (SV) and Copy Number Variants (CNV) Detection
    Explore methods to detect larger genetic changes, including structural variations and copy number variations, which are crucial for understanding genome structure.
  4. Population Genetic Analysis
    Explore techniques for constructing phylogenetic trees, applying principal component analysis (PCA) for data dimensionality reduction, and analyzing population structure to understand evolutionary relationships, genetic diversity, and ancestral lineage within populations.
  5. Genome-Wide Association (GWA) Study
    Understand how to conduct GWAS to link specific genetic variants with traits of interest across populations.
  6. Genome-Environment Association (GEA) Analysis
    Learn to perform GEA, associating genetic variation with environmental factors to understand local adaptation.
  7. Population Selection Analysis
    Calculate nucleotide diversity (π), a measure of genetic variation within a population, critical for population genetics studies. Use Tajima’s D to test for neutrality in evolution and detect selective sweeps or population bottlenecks. Explore the calculation of FST (Fixation Index), a measure of population differentiation, to assess genetic divergence among populations.

License and Copyright

Copyright (C) 2024 Xingwan Yi, Amy Kim, Zhiqin Long, Yue Yu.

The materials are distributed under the CC BY 1.0 License.

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