Course Overview
Course Integrity
This course is compiled automatically on 2021-03-19
The course is tested and available on MacOS, Windows and Ubuntu Linux for R version 4.0.3 (2020-10-10)
Overview
This course introduces key methods for Genomic Visualization using Bioconductor.
In the first two sessions we will cover the visualization of genomic loci as tracks using Gviz.
In the final 2 sessions we will review methods to simultaneously visualize multiple loci across groups and/or conditions.
Setting up
System Requirements
Install R
R can be installed from the R-project website.
The R website can be found here http://www.r-project.org/.
The download links and associated installation instructions for multiple platforms can be found below provided by Revolution Analytics. https://cran.revolutionanalytics.com
We recommend installing R 4.0.3 as this is the version used to compile the course. Direct downloads for R 4.0.3 for the main platforms can be found below:
Install RStudio
RStudio can be installed from the RStudio website.
RStudio can be downloaded for all platforms at the link below
https://rstudio.com/products/rstudio/download/
Install required packages
From the course package
install.packages('BiocManager')
BiocManager::install('RockefellerUniversity/RU_VisualizingGenomicsData',subdir='VizualizingGenomicsData')From CRAN and Bioconductor
install.packages('BiocManager')
BiocManager::install('Rsamtools')
BiocManager::install('GenomicAlignments')
BiocManager::install('TxDb.Mmusculus.UCSC.mm10.knownGene')
BiocManager::install('org.Mm.eg.db')
BiocManager::install('Gviz')
BiocManager::install('rtracklayer')
BiocManager::install('TxDb.Mmusculus.UCSC.mm9.knownGene')
BiocManager::install('DESeq2')
BiocManager::install('tximport')
BiocManager::install('goseq')
BiocManager::install('DEXSeq')
BiocManager::install('limma')
BiocManager::install('IRanges')
BiocManager::install('TxDb.Hsapiens.UCSC.hg19.knownGene')
BiocManager::install('GenomicFeatures')
BiocManager::install('BSgenome.Mmusculus.UCSC.mm10')
BiocManager::install('biomaRt')
BiocManager::install('BSgenome.Hsapiens.UCSC.hg19')
BiocManager::install('vsn')
BiocManager::install('ChIPQC')
BiocManager::install('MotifDb')
BiocManager::install('seqLogo')
BiocManager::install('pheatmap')
BiocManager::install('soGGi')
BiocManager::install('profileplyr')
BiocManager::install('NbClust')
BiocManager::install('knitr')
BiocManager::install('rmarkdown')
BiocManager::install('testthat')
BiocManager::install('yaml')The Presentations
Introduction to Gviz - part1
This section introduces the visualization of Genomics data in Bioconductor Session sections:
- Introduction to Gviz
- Plotting genomic signal from bigWigs
- Visualization of annotation and genomic models
Links to presentations:
The html slide presentation can be found at this link Slide
The single page html presentation can be found at this link Single Page
The code use in the presentations can be found at R code
Introduction to Gviz - part2
This section introduces the visualization of Genomics data in Bioconductor Session sections:
- Plotting aligned reads from BAM
- Visualization of external data from Biomart and UCSC
Links to presentations:
The html slide presentation can be found at this link Slide
The single page html presentation can be found at this link Single Page
The code use in the presentations can be found at R code
Introduction to Gviz - part3
This section introduces the visualization of Genomics data in Bioconductor Session sections:
- Plotting heatmaps for RNAseq
- Dimension reduction using PCA
Links to presentations:
The html slide presentation can be found at this link Slide
The single page html presentation can be found at this link Single Page
The code use in the presentations can be found at R code
Introduction to Gviz - part4
This section introduces the visualization of Genomics data in Bioconductor Session sections:
- Epigenetic and motif profiles
- Profileplyr heatmaps
Links to presentations:
The html slide presentation can be found at this link Slide
The single page html presentation can be found at this link Single Page
The code use in the presentations can be found at R code
Getting help
Course help
For advice, help and comments for the material covered in this course please contact us at the issues page associated to this course.
The link to the help pages can be found here
General Bioinformatics support
If you would like contact us about general bioinformatics advice, support or collaboration, please contact us the Bioinformatics Resource Center at brc@rockefeller.edu.