Authors:
Jacques Serizay^[Institut Pasteur, Paris],
Last modified: 2024-07-23.
By adhering to the principles of tidy data organization and the elegant syntax
of tidyverse packages, researchers can navigate the complexities of genomic
datasets with unprecedented ease and efficiency.
In this workshop, we will go over three recent packages:
plyranges, developed to manipulate generic genomic ranges within thetidyomicsframework;plyinteractions, specifically developed to manipulate chromatin conformation capture (3C, Hi-C micro-C, etc);tidyCoverage, to manipulate and extract coverage tracks within thetidyomicsframework.
plyinteractions and tidyCoverage packages introduce novel
SummarizedExperiment-derived S4 classes to store genomics data and expand
tidy methods, following the principles defined in plyranges and
tidySummarizedExperiment.
They synergize the existing functionalities of tidyverse and
Bioconductor, to seamlessly intertwine data manipulation, aggregation,
visualization, and modeling within a unified framework.
This 90min-long workshop will include brief overview of some of the state-of-the-art packages
following the tidyomics ecosystem recommendations. Most of the workshop will
be based on a combination of instructor-led live demo and hands-on guided exercises.
- Knowledge of
GenomicRangesandSummarizedExperimentclasses of object - Familiarity with standard genomic processed data formats (e.g.
bedfiles,bigwigfiles, ...)
The following resources are relevant to this workshop:
- tidyomics Nat. Methods paper
- plyranges Genome Biol. paper
- tidyCoverage Bioinformatics paper (in press)
plyrangesplyinteractionstidyCoverage
| Activity | Time |
|---|---|
| Manipulating genomic ranges data | 20m |
| Manipulating genomic interaction data | 35m |
| Manipulating coverage data | 35m |
Learning goals:
- Manipulate genomic features, genomic interactions and/or genomic tracks using
tidyomicsprinciples; - Integrating different levels of genomic information together.
Learning objectives:
- Import/coerce genomic features and/or interactions into relevant Bioconductor classes;
- Summarize genomic information using tidy data approaches;
- Visualize and aggregate genomic coverage data over genomic features of interest in a tidy manner.
The companion website for this workshop is available here:
https://js2264.github.io/Bioc2024tidyworkshop
To use the workshop image:
docker run -e PASSWORD=<choose_a_password_for_rstudio> -p 8787:8787 ghcr.io/js2264/bioc2024tidyworkshop:latestOnce running, navigate to http://localhost:8787/ and then login with rstudio:yourchosenpassword.