I used Tximeta to import a summarisedExperiment from the salmon output (used with genocide transcriptome v34). I need to produce 4 matrix of counts: - tx counts in TPM - gene counts in TPM - tx counts normalised - gene counts normalised
The first two I used
assay(se, "counts") and
assay(gse, "counts") respectively.
Mu problem is to apply the normalisation to them. I used deseq2 to estimate the size factors with a fake design because there are no groups yet in the dataset so I used ~gender to been able to generate a adds object to apply the
EstimateSizeFactor, but when I try to see them returns me 'NULL'
> dds_genes <-DESeqDataSet(gse, design = ~ gender) > dss_genes <- DESeq2::estimateSizeFactors(dss_genes) > DESeq2::sizeFactors(dss_genes)  NULL
I get count values like this after using these commands (which I am not really sure they are really normalised;
normalized_counts <- DESeq2::counts(dss_genes, normalized=T) normalized_counts[1:10, 1:10] ENSG00000000003.15 654.92903 771.34051 500.1863 560.30530 1144.8295 938.40446 1173.208233 896.28964 388.1482 501.20545 ENSG00000000005.6 0.00000 0.00000 0.0000 0.00000 0.0000 0.00000 1.344747 0.00000 0.0000 0.00000 ENSG00000000419.12 416.59305 399.05434 675.0911 285.64627 551.8253 424.59423 461.448691 679.08099 365.8343 461.66276 ENSG00000000457.14 242.52226 244.91792 279.9109 414.24494 262.8790 354.50834 451.671501 427.08499 407.7070 329.50667
I don't know how to proceed to just get a TMM normalised values from tximeta object. That would be my preferred option. I guess deseq2 can also provide me with normalised data.
Maybe there are other ways?
Thank you for the help!!