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- When creating RNA-Seq libraries, you have lots of options: strand specific vs non strand specific, ribosomal depletion , polyA enrichment, random priming etcetc.
- Decisions depend on your questions.
- For differential expression studies, number of replicates is most important. For assembly and annotation of transcriptomes or for identifying rare/novel transcripts, depth of coverage becomes important.
Once you get your RNA-Seq data
- Check for low quality bases, low quality reads, overrepresented sequences, and sequence duplication using fastqc.
- If needed, trim low quality bases, filter low quality reads, trim adaptors. We covered fastx_toolkit and cutadapt for doing these operations.
- Now it's ready for mapping.
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