DESeq2
also allows for the analysis of complex designs.
We heavily encourage trainees to read the entire DESeq2
vignette to learn more:
https://bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.html
Briefly, a few examples may include the need to control for
variables, such as a batch effect or biological variable (e.g.: sex, age
etc.). The standard process through which this can be performed in
DESeq2
is by including the additional variable(s) as part
of the design. For example, the following design would test for
differences in a variable called condition
, while
controlling for batch
.
design= ~ batch + condition
Note: Does the order of variables matter?
The best practice for DESeq2
is to add your variable of
interest (to be tested for DEG analysis), at the last position in the
design (as shown in the example above). This order aids in ensuring that
default results are pulled from the variable of interest.
DESeq2
can be used to analyze time course experiments.
This
workflow is a great introduction for this type of analysis.
While DESeq2
is a great tool for many RNA-seq analysis,
it also has its limitations. One particular limitation to be aware
of is that it does not support differential expression analysis with
random effects. A great resource for this type of analysis, is
limma
(specifically limma-voom
). While the
limma
vignette can be quite large due to its historical
role in microarray data, it’s well organized and searchable to direct
users to RNA-seq data and it’s limma-voom
approach.
See more at: http://bioconductor.org/packages/release/bioc/vignettes/limma/inst/doc/usersguide.pdf
As discussed, secondary analysis with nf-core pipelines already implement what is known as software containers (Docker, Singularity), however tertiary analysis and visualization requires users to build their own custom containers. This can be a critical step in aiding your analysis to be portable and reproducible.
Unfortunately, due to time limitations and workshop scope, we are unable to demonstrate how to build your own containers. To learn more about Docker and Singularity containers, we encourage all trainees to visit our training website for a detailed 3-part tutorial in the “Intro to Docker with RStudio” tab from https://u-bds.github.io/training_guides/.
If you have follow-up questions about this workshop or any other data science topic which cover domain that U-BDS cover, please attend our office hours.
It is every Thursday from 1:30pm-2:00. The registration link can be found here.
If you would like to learn more about the core services please visit our main UAB webpage at: https://www.uab.edu/cores/ircp/bds. If you would like to have a consultation, please fill out the “Enquiry Form” present on the website.