Post Transcriptome Assembly Downstream Analyses
Once your assembly is complete, there are several analyses you will likely want to pursue to explore aspects of the biology of your organism based on your assembled transcripts and the input RNA-Seq data. Such studies might include:
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Quantifying transcript and gene abundance. This is a prerequisite to many other analyses such as examining differentially expressed transcripts among your samples.
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Quality checking your samples and biological replicates. Make sure the relationships among your samples and biological replicates make sense. If there are any confounding aspects to the data, such as outliers or batch effects, you'll want to catch them as early as possible and account for them in your further data explorations.
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Perform differential expression analysis. Trinity provides direct support for several DE analysis methods, including edgeR, DESeq2, Limma/Voom, and ROTS.
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Extract coding regions using TransDecoder and functionally annotate the transcripts using Trinotate.
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If your organism has an assembled genome, consider using the Trinity transcriptome assemblies for gene structure annotation using PASA.
- Trinity Wiki Home
- Installing Trinity
- Running Trinity
- Trinity process and resource monitoring
- Output of Trinity Assembly
- Assembly Quality Assessment
- Downstream Analyses
- Miscellaneous additional functionality that may be of interest
- Contributing code
- Trinity Tidbits
- Frequently Asked Questions (FAQ)
- There are too many transcripts! What do I do?
- How to minimize RAM usage
- How do I use reads I downloaded from SRA
- How do I identify the specific reads that were incorporated into the transcript assemblies?
- How can I perform cross-species analysis?
- How do I combine PE and SE reads?
- How can I run this in parallel on a computing grid?
- Computing and Time requirements
- Errors during Trinity run
- Killing Trinity
- Contact us