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.
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
We will be working through some tutorials directly on your laptop using R.
- 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)
-
- If you have not done so already, update your local copy of the class repository from GitHub. You should have a directory (
lecture15
) containing the following three R tutorials:- R Markdown files
- Lecture15_GenomicData.Rmd: store genomic data as objects, assess genomic ranges, apply operations on genomic data
- Lecture15_VariantCalls.Rmd: load and assess variant (vcf) data
- Jupyter Notebook files
- R Markdown files
- 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 namedGIAB_highconf_v.3.3.2.vcf
, look in your Trash folder to find the original file ending ingz
)GIAB_highconf_v.3.3.2.vcf.gz.tbi