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Lecture 15: Genomic data in R

This lecture will unite the last lecture's content on genomic analysis with our previous coding in R. The packages we'll use this week are from Bioconductor, a collection of software specifically designed for genomic analysis in R.

Lecture Notes

Lecture slides

Learning objectives

Genome variant analysis (Background)

  • Types of genomic variation
  • Tools to predict genomic variations
  • Learn the common file formats for variation data
  • Databases and online resources for human variation data

Genomic Data (hands-on tutorials)

  • Use Bioconductor packages to work with genomic data in R
  • Load, inspect, and query genomic data (BED/SEG, VCF files)
  • Identify and annotate genomic variants

Before the class

We will be working through some tutorials directly on your laptop using R.

1. Install the R packages

  • Tutorial is tested for R-4.0.3
  • You will need the Docker container containing the correct version of R and the required R packages already installed.
  • This these packages:
    • GenomicRanges: manipulating genomic data

    • plyranges: fast & easy tool for mannipulating GRanges

      ## start R session ##
      R
      ## check that these packages can be loaded successfully ##
      library(tidyverse)
      library(GenomicRanges)
      library(plyranges)
      

2. Class materials: R Markdown and Jupyter Notebook files containing the tutorials

3. Class materials: Genomic and sequencing data for the tutorials

  • Please download all data files found in this folder and add them to your lecture15 directory. The files should have the following filenames:
    • BRCA.genome_wide_snp_6_broad_Level_3_scna.seg
    • GIAB_highconf_v.3.3.2.vcf.gz (if this file was automatically uncompressed on your computer, resulting in a file named GIAB_highconf_v.3.3.2.vcf, look in your Trash folder to find the original file ending in gz)
    • GIAB_highconf_v.3.3.2.vcf.gz.tbi