Let's recap what we learned on Day 3:
APart 1. Annotated genes/transcripts
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- MA plots, heat maps, PCA are all good ways to visualize your gene expression data. Make sure to use normalized, log transformed data for these visualizations.
BPart 2. Novel transcripts
Use a pipeline of hisat2 (mapping to genome), stringtie (transcript assembly, quantification), and ballgown (differential expression testing)
- If you want to identify novel transcripts in your particular samples
- If you want to look for differential expression in these novel transcripts
Part 3. Tag-Seq
Tag-See is targeted sequencing of just the 3' ends of mRNA.
- This is done at GSAF using a template switching protocol.
- It offers a reduction in library prep and sequencing cost.
- Consider it when looking to do differential expression analysis of known genes with more replicates, conditions, timepoints etc.
- Analysis involves some extra preprocessing. Other steps are similar to standard RNA-Seq analysis.
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