Considerations for reference vs reference-free transcriptome analysis¶
Whether you work with microbes that have a sequence reference genome or you have one without a reference, please know that there are several reasonably complete workflows that you can use for both types of analyses. No need to re-invent the wheel.
We will attempt to cover both approaches using available workflows and then point you to additional resources so that you can choose the one that best fits your needs.
Reference-based transcriptome analysis¶
The general approach for reference-based (if you already have an available sequenced genome) is as follows (can use different tools though):
Several workflows can be utilized for this type of analysis, including:
- SPARTA - sparta.readthedocs.org
- Rockhopper - http://cs.wellesley.edu/~btjaden/Rockhopper/
- Galaxy (drag and drop cloud computing GUI interface for NGS data analysis) - https://galaxyproject.org/
- Several others not necessarily mentioned here but a Google search can help
Reference-free transcriptome analysis¶
The approach for reference-free (no good reference genome and not enough pre-existing mRNA-seq data for assembled transcriptomes) is an entirely different animal than reference-based approaches. The process is related and generally can follow this type of workflow (this is an example from eukaryotes):
This is usually an iterative process that may require additional tools and computational time to work through the data. But it can be done! A useful presentation from Meg Staton on de novo assembly.
There are fewer workflows readily available for de novo transcriptome assembly:
- Rockhopper2 - http://cs.wellesley.edu/~btjaden/Rockhopper/
- khmer and Trinity - http://khmer.readthedocs.org/en/v2.0/ and http://trinityrnaseq.github.io/
- Galaxy (drag and drop cloud computing GUI interface for NGS data analysis) - https://galaxyproject.org/
- What we will show today as a brief example
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