Hello,
I have a question regarding transformation and/or normalization as it applies to analysis of differential expression (DE) for a non-model (novel) de novo assembled transcriptome.
(1) I have an assembled transcriptome that I'm happy with - let's not get into that
(2) For DE analysis, does one have to do both a transformation and normalization, or can one simply do one or the other - depending on the downstream questions / analysis? Or are these two totally different things that can be mutally exclusive?
(3) For DE analysis, it seems (and here's where my understanding is sketchy) that some of the normalization methods are better suited to organisms whose genomes are gene annotated. Because I'm using the circular approach of making a transcriptome from the reads and then using that (transcriptome) as the reference, some of the approaches to normalization would likely (maybe) not apply. I know that RSEM used in conjunction with Trinity (Broad Institute) uses TMM. Would RPKM also (not in addition to) still be a relavent normalization approach for DE analysis of transcriptome data? Or would RPKM inadvertently up the small transcripts?
Thanks,
Andor
I have a question regarding transformation and/or normalization as it applies to analysis of differential expression (DE) for a non-model (novel) de novo assembled transcriptome.
(1) I have an assembled transcriptome that I'm happy with - let's not get into that
(2) For DE analysis, does one have to do both a transformation and normalization, or can one simply do one or the other - depending on the downstream questions / analysis? Or are these two totally different things that can be mutally exclusive?
(3) For DE analysis, it seems (and here's where my understanding is sketchy) that some of the normalization methods are better suited to organisms whose genomes are gene annotated. Because I'm using the circular approach of making a transcriptome from the reads and then using that (transcriptome) as the reference, some of the approaches to normalization would likely (maybe) not apply. I know that RSEM used in conjunction with Trinity (Broad Institute) uses TMM. Would RPKM also (not in addition to) still be a relavent normalization approach for DE analysis of transcriptome data? Or would RPKM inadvertently up the small transcripts?
Thanks,
Andor
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