Hi,
I have run an RNAseq analysis and am stuck on what would be the most appropriate thing to report in results.
I first decided to report the results of IHW tested results from DESeq2, from reading the vignettes this output is suggested to be a better method than the default results output by DESeq2. Is this correct?
Secondly, I applied apeglm shrinkage to my dds object for plotting a MA plot, because from reading the vignettes this output is suggested to be a better shrinkage than the default shrinkage output by DESeq2.
However I am getting confused by which results to finally report.
I am hoping to sort my results by the most robust changes (significnace value) in my dataset as many of my genes have a LFC of >2 in all results.
Should I output apeglm results and report the associated s values? or should I use IHW results and report the associated adj.pvalues?
OR should I output apeglm results and report the associated adj.pvalues?
Which is the 'gold standard' or best course of action?
Fot the latter, svalues = FALSE, doesn't seem to be working for me to produce padj values when I run my dds object through lfcshrink()
> res.sLFC <- lfcShrink(dds.s, coef="comparison_disease_vs_Control", svalue = FALSE, type="apeglm", lfcThreshold=1)
using 'apeglm' for LFC shrinkage. If used in published research, please cite:
Zhu, A., Ibrahim, J.G., Love, M.I. (2018) Heavy-tailed prior distributions for
sequence count data: removing the noise and preserving large differences.
Bioinformatics. https://doi.org/10.1093/bioinformatics/bty895
computing FSOS 'false sign or small' s-values (T=1)
> res.sLFC
log2 fold change (MAP): comparison PPCD vs Control
DataFrame with 31172 rows and 4 columns
baseMean log2FoldChange lfcSE svalue
<numeric> <numeric> <numeric> <numeric>
ENSG00000000003 30899.27765 -2.980110 0.313910 1.14037e-11
ENSG00000000005 2.92703 -3.052505 1.084273 4.83066e-03
ENSG00000000419 2457.80966 0.288835 0.164714 7.25880e-01
ENSG00000000457 1310.70709 -0.930851 0.182720 2.58388e-01
ENSG00000000460 417.26650 0.919899 0.334406 2.23694e-01
... ... ... ... ...
ENSG00000288584 2.418664 -0.21016742 0.713188 0.536877
ENSG00000288585 10.382099 0.00861317 0.381028 0.678976
ENSG00000288586 13.772947 -0.34706693 0.427470 0.613719
ENSG00000288587 8.671689 0.01334065 0.859633 0.553893
ENSG00000288588 0.715984 -0.34188076 0.952566 0.358753
Many thanks for any assistance,
Nathan
Answered on Bioconductor: https://support.bioconductor.org/p/131563/#131566