tfcb_2020

Lecture 16: 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

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

Before the class

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

1. Install the R packages

Tutorial is tested for R-4.0.3
You should run this script in RStudio to ensure all Bioconductor packages are installed.
This script will install the following packages:
- Rsamtools: querying BAM files
- VariantAnnotation: reading VCF files
- GenomicRanges: manipulating genomic data

2. Class materials: R Markdown files containing the tutorials

If you have not done so already, update your local copy of the class repository from GitHub. You should have a directory (lecture16) containing the following three RMarkdown tutorials:
- Lecture16_GenomicData.Rmd: store genomic data as objects, assess genomic ranges, apply operations on genomic data
- Lecture16_Rsamtools.Rmd: load and query sequencing data; compute “pile-up” statistics at genomic loci to identify genomic variants
- Lecture16_VariantCalls.Rmd: load and assess variant (vcf) data

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

Please download all data files found in this folder and add them to your lecture16 directory. The files should have the following filenames:
- BRCA.genome_wide_snp_6_broad_Level_3_scna.seg
- BRCA_IDC_cfDNA.bam
- BRCA_IDC_cfDNA.bam.bai
- 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