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Which pipeline is the best for differentinal gene expression analysis (edgeR, DESEQ2 or HISAT2 - stringtie - ballgown)?

HI, I may asking a naive question, to clarify myself. Which RNA_seq pipeline considered to be the best for model and non-model organisms ? I used edgeR earlier, find it very easy. Can some one explain, which pipeline is the best edgeR, DESEQ2 or HISAT2 - StringTie - Ballgown How to select these tools on what criteria ? Some simple answers.

rna-seq

1 answer

It'll strongly depend on your data. If you have a good genome of reference (e.g. human) and you are interested in to study differential transcript usage and discover new potential isoforms, the best idea is Hisat2-StringTie-Ballgown. If you are only interested in study differential gene expression and potential implications like GO enrichment and KEGG, use Rsubread and edgeR is the best option (time and computation resources consuming with strong statistical backup).

Thanks,I'm working with non-model organism, only primary genome assembly (26 replicons) available currently. I'm interested only in the differential gene expression analysis. I started with TRINITY,HISAT2,featurecounts,edgeR,GO,KEGG.

Trinity is a transcriptome de novo assembler... Do you really need that if you have got a genome of reference?

I don't have alternate assembly, the non-model organism I'm working.

It may be easier use salmon + edgeR afeter the assembly and annotation (Trinity-Trinotate)

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