RNA seq result interpretation

Question: RNA seq result interpretation

2.5 years ago by

reena_gd • 0 wrote:

Hello, I am doing RNAseq analysis for the first time. I have two samples, control and treatment of a plant variety collected at 14 days interval. I obtained few data sets of differentially expressed genes which had similar gene ID and were also the same transcripts. They were same except that, they differed in FPKM values and had different regulation, like one is up-regulated (12-fold) and other is down-regulated (13-fold). I assume that minor variation errors could be possible but such fold variation along with up-regulation and down-regulation cannot be overlooked. I also don’t think that they could be different fragments of the same transcript as they show different regulation. Can anyone suggest the reason for such data? Or is this mere an error.

rna-seq next-gen • 908 views

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written 2.5 years ago by reena_gd • 0

Large log fold-changes are often observed in RNA-seq data that has undergone FPKM normalisation, even as high as +90, but this is more due to the inadequacies of this normalisation strategy than anything else. For one, FPKM does not normalise across samples and is therefore not adequately adjusting for different library sizes. Variance will, as you implied, also affect all statistical calculations and values - from what I understand, FPKM normalisation neither deals very well with variance.

If you can obtain raw counts, my advice is to get those, and then work from those using a 'better' normalisation strategy.

ADD REPLY • link written 2.5 years ago by Kevin Blighe ♦ 61k

Thanks Kevin, I tried another strategy, but results are not much varying than previous. I suppose removing such ambiguous data would be better.

ADD REPLY • link written 2.5 years ago by reena_gd • 0

Which was the other strategy? Have you checked for sample outliers via something like a PCA bi-plot?

ADD REPLY • link written 2.5 years ago by Kevin Blighe ♦ 61k

I don't think these could be outliers because several other genes have similar up and down regulation values. I have

                                  GENE_MODEL_ID       RefSeq_ID                 control read count          treated read count
TCONS_00047959        XLOC_028640             XM_003535153.3          135.743                       0.00891439                                                                               
TCONS_00047960        XLOC_028640             XM_003535153.3         0.00996383                         70.1898

I expect TCONS ID differed because it is generated for each different transcript in each experiment

ADD REPLY • link modified 2.5 years ago by Kevin Blighe ♦ 61k • written 2.5 years ago by reena_gd • 0

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