Visualization of RNA-Seq results with CummeRbund

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# Visualization of RNA-Seq results with CummeRbund

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		<a href="/training-material/hall-of-fame/bagnacan/" class="contributor-badge contributor-bagnacan"><img src="https://avatars.githubusercontent.com/bagnacan?s=36" alt="Andrea Bagnacani avatar" width="36" class="avatar" />
    Andrea Bagnacani</a>
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## Requirements

Before diving into this slide deck, we recommend you to have a look at:

- [Introduction to Galaxy Analyses](/training-material/topics/introduction)

- [Sequence analysis](/training-material/topics/sequence-analysis)
    - Quality Control: [<i class="fab fa-slideshare" aria-hidden="true"></i><span class="visually-hidden">slides</span> slides](/training-material/topics/sequence-analysis/tutorials/quality-control/slides.html) - [<i class="fas fa-laptop" aria-hidden="true"></i><span class="visually-hidden">tutorial</span> hands-on](/training-material/topics/sequence-analysis/tutorials/quality-control/tutorial.html)
    - Mapping: [<i class="fab fa-slideshare" aria-hidden="true"></i><span class="visually-hidden">slides</span> slides](/training-material/topics/sequence-analysis/tutorials/mapping/slides.html) - [<i class="fas fa-laptop" aria-hidden="true"></i><span class="visually-hidden">tutorial</span> hands-on](/training-material/topics/sequence-analysis/tutorials/mapping/tutorial.html)

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### <i class="far fa-question-circle" aria-hidden="true"></i><span class="visually-hidden">question</span> Questions

- How are RNA-Seq results stored?

- Why are visualization techniques needed?

- How to select our desired subjects for differential gene expression analysis?

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### <i class="fas fa-bullseye" aria-hidden="true"></i><span class="visually-hidden">objectives</span> Objectives

- Manage RNA-Seq results

- Extract the desired subject for differential gene expression analysis

- Visualize information

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# Why visualization?

???
Data alone does not bring any information: to carry information, data needs to be contextualized. Transcriptomic data is no exception, therefore to organize the growing body of knowledge pertaining RNA-Seq experiments and infer valuable insights, data needs to be organized, annotated, and ultimately visualized.

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### Where is my data coming from?

![Wang et al, Nat Rev Genet, 2009](../../images/transcriptomics_images/cummerbund-rna-seq-experiment.jpg)

<small>[*Wang et al, Nat Rev Genet, 2009*](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2949280/)</small>

???
- RNAs are converted into cDNA fragments through RNA fragmentation
- sequencing adaptors (in blue) are then added to each cDNA fragment
- cDNA sequences are obtained via NGS sequencing
- the obtained reads are subsequently aligned against a reference genome or transcriptome, and classified in-silico as exonic reads, junction reads, and poly-A reads
- these three types are then used to outline an expression profile for each gene

This is the process that will:

- reveal new genes and splice variants
- help quantifying cell-specific gene expression within the genome under study

But once this pipeline is implemented, how are sequence data going to be analysed and managed?

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### Bioinformatic tools for RNA-Seq analysis

Once the RNA-Seq pipeline is implemented, we still need to handle and analyse all data that is generated. This requires:

- computer science skills to be handled

- mathematical knowledge to be interpreted

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### Bioinformatic tools for RNA-Seq analysis

![Trapnell et al, Nat Protoc, 2012](../../images/transcriptomics_images/cummerbund-rna-seq-experiment-tuxedo.jpg)

<small>[*Trapnell et al, Nat Protoc, 2012*](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3334321/)</small>
???
- first, reads from each condition are mapped to the reference genome using TopHat
- the resulting alignment files are given to Cufflinks, which generates a transcriptome assembly for each condition
- the two assemblies are then merged together to provides a uniform basis for calculating of gene and transcript expression in each condition
- both reads and merged assemblies are fed to CuffDiff, to calculate expression levels via statistical significance test for the observed changes

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### Bioinformatic tools for RNA-Seq analysis

The last step in our RNA-Seq analysis is CuffDiff. Its output comprises multiple files containing the results of the differential expression analysis.

- Gene expression levels are reported as <i>tab-separated</i> values: a simple tabular output that can be viewed with any spreadsheet application. Such files contain statistics, gene-related, and transcript-related attributes
.image-75[![CuffDiff output](../../images/transcriptomics_images/cummerbund-cuffdiff-output.png)]

- Another way to collect all these data is to organize it within a dedicated database for later consultation. CuffDiff can be instructed to do so
.image-50[![CuffDiff output SQLite](../../images/transcriptomics_images/cummerbund-cuffdiff-set-sqlite.png)]

???
- CuffDiff provides analyses of differential expression and regulation at the gene and transcript level
- its results are reported in a tab separated format
- the overall collection of data is difficult to read to obtain a bird's-eye view of the change of expression
- the data can be organized in a SQLite database

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### Bioinformatic tools for RNA-Seq analysis

Whatever storage strategy you opted for, i.e. multiple tab-separated-value files or a SQLite database, all data is still retained within text format.

We need to have a bird's-eye view of that data, and <i>make sense</i> of it

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# Visualization

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### CummeRbund

[CummeRbund](http://compbio.mit.edu/cummeRbund/) is an R package for visualizing the results of a CuffDiff output.

- Manages, integrates, and visualizes all data produced by CuffDiff

- Simplifies data exploration

- Provides a bird's-eye view of the expression analysis

- Helps creating publication-ready plots

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### CummeRbund

CummeRbund needs to be instructed on which data to be visualized:

- <i>Extract CuffDiff</i>'s "Transcript differential expression testing" table

- <i>Filter</i> the table on the column storing the significance of a differentially expressed gene

- <i>Sort</i> all entries on the basis of most significant differentially expressed gene

- Identify the most significant differentially expressed gene

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### CummeRbund

Once the most significant differentially expressed gene has been identified, CummeRbund can generate publication-ready plots to highlight...

.image-50[![CummeRbund Expression plot](../../images/transcriptomics_images/cummerbund-expression-plot.png)]

The expression of all isoforms of the single gene with replicate FPKMs

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### CummeRbund

Once the most significant differentially expressed gene has been identified, CummeRbund can generate publication-ready plots to highlight...

.image-50[![CummeRbund Expression plot](../../images/transcriptomics_images/cummerbund-expression-bar-plot.png)]

The expression bar-plot of all isoforms of a gene with replicate FPKMs

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### CummeRbund

...and many more

.image-50[![Other CummeRbund plots](../../images/transcriptomics_images/cummerbund-other-plots.png)]

Have a look at [CummerBund's tutorial](https://bioconductor.org/packages/2.11/bioc/vignettes/cummeRbund/inst/doc/cummeRbund-manual.pdf) to overview all possibilities!

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### <i class="fas fa-key" aria-hidden="true"></i><span class="visually-hidden">keypoints</span> Key points

- Extract informations from a SQLite CuffDiff database

- Filter and sort results to highlight differential expressed genes of interest

- Generate publication-ready visualizations for RNA-Seq analysis results

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## Thank You!

This material is the result of a collaborative work. Thanks to the [Galaxy Training Network](https://training.galaxyproject.org) and all the contributors!

<div class="contributors-line">
		Authors: <a href="/training-material/hall-of-fame/bagnacan/" class="contributor-badge contributor-bagnacan"><img src="https://avatars.githubusercontent.com/bagnacan?s=36" alt="Andrea Bagnacani avatar" width="36" class="avatar" />
    Andrea Bagnacani</a>
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Tutorial Content is licensed under <a rel="license" href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International License</a>.<br/>