GWASTutorial
76 R resources
GitHub
  • Home
  • Command Line
  • Pre-GWAS
  • GWAS
  • Post-GWAS
  • Topics
  • Assignments
  • Recommended reading
GitHub
    • Tutorial guide
    • Introduction
    • Overview
    • About
    • Update Log
    • Programming for GWAS
      • Linux Basics
      • Windows Linux Subsystem
      • SSH
      • Job scheduler
      • Text editing - awk
      • Text editing - sed
      • Linux Resources
      • Python Basics
      • Python Resources
      • Anaconda
      • Jupyter notebook
      • R Basics
      • R Resources
      • Git and github
    • 1000 Genomes Project
    • Sample Dataset
    • Data Formats
    • Genotype Data QC
    • Sample PCA
    • PCA Visualization
    • Phasing
    • Imputation
    • Association tests by PLINK
    • Visualization by gwaslab
    • Linear mixed model (LMM)
    • Saddlepoint approximation by SAIGE
    • Whole genome regression by REGENIE
    • Rare variant association tests
    • Post-GWAS Analysis Overview
    • Annotation by ANNOVAR & VEP
    • SNP-heritability estimation by GREML
    • LD score regression by LDSC
    • Gene/Gene-set tests by MAGMA
      • Fine-mapping Basics
      • SuSIE Fine-mapping Tutorial
    • Meta-analysis
      • PRS Basics
      • PRS evaluation
      • MR Basics
      • TwoSampleMR Tutorial
    • Conditional analysis
    • Colocalization
    • TWAS (using FUSION)
    • Single-cell genomics integration
    • Allele
    • Linkage Disequilibrium (LD)
    • Heritability Concepts
    • Statistical power
    • Winner's curse
    • Bias
    • Relatedness and sample structure
    • Phenotype normalization
    • Measure of effect
      • Coordinate Systems
      • Liftover
      • UCSC LiftOver Tool
    • Assignment - 1KG PCA
    • Assignment - Presentation
  • Recommended reading
  1. GWASTutorial
  2. Command Line
  3. R

76 R resources

  • R Programming for Data Science : https://bookdown.org/rdpeng/rprogdatascience/
GWASTutorial is licensed under the MIT license
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