Hello everyone/ RECOUNT3/ DEseq2,

Before i raise this question, i kind of read some previous post (Counts from recount3 for DESeq2 analysis) about DEseq2 and RECOUNT3 object. But i am still have no idea how to do it or is it possible doing so.

Therefore, my question is is it possible and how to combine 2 rse objects download from Recount3 and perform DEseq2 analysis on 2 different datasets, for example, between cancer and GTEx normal tissue? Also, if it is possible, how can i tell/ what is the code to tell DEseq2 function the 2 conditions that i want to compare? I basically cannot translate what i learnt from DEseq2 tutorial (http://bioconductor.org/packages/devel/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#summarizedexperiment-input) and apply to what i am doing.

I apologize if my question is not good and my coding basic is weak as a biologist. I have attached some detail of the datasets below as reference. Thank you everyone for your help.

Best Regards, David LIU

Code should be placed in three backticks as shown below

# this is the detail of the rse from normal tissue from RECOUNT3:

> rse_GTEx_Brain_tissuex
class: RangedSummarizedExperiment 
dim: 63856 224 
metadata(8): time_created recount3_version ... annotation recount3_url
assays(4): raw_counts counts RPKM TPM
rownames(63856): ENSG00000278704.1 ENSG00000277400.1 ...
  ENSG00000182484.15_PAR_Y ENSG00000227159.8_PAR_Y
rowData names(10): source type ... havana_gene tag
colnames(224): GTEX-14LZ3-0011-R10b-SM-6AJA9.1
  GTEX-17HII-0011-R10a-SM-79OMY.1 ... GTEX-1GTWX-0011-R10b-SM-CJI2X.1
  GTEX-1HCU6-0011-R10a-SM-CKZP8.1
colData names(198): rail_id external_id ... recount_seq_qc.errq BigWigURL

#this is the rse detail for a cancer dataset  from RECOUNT3

>rse_TCGA_CANCER
class: RangedSummarizedExperiment 
dim: 63856 175 
metadata(8): time_created recount3_version ... annotation recount3_url
assays(3): raw_counts counts TPM
rownames(63856): ENSG00000278704.1 ENSG00000277400.1 ...
  ENSG00000182484.15_PAR_Y ENSG00000227159.8_PAR_Y
rowData names(10): source type ... havana_gene tag
colnames(175): 3b7f80e6-74a7-4da1-ac4b-c260b6be880a
  97a8e2b1-059b-4527-8fb4-116f718ffd16 ...
  2dab6792-f9af-4565-bdd5-c9802f3132f4 c33edb64-c7b9-49a1-ae73-1d293f8522f6
colData names(937): rail_id external_id ... recount_seq_qc.errq BigWigURL

#In DEseq2 tutorial, from what i understand, there seem to be a few ways to tell what condition DEseq2 should do comparison with, like:

library("airway")
data("airway")
se <- airway

library("DESeq2")
ddsSE <- DESeqDataSet(se, design = ~ cell + dex)
ddsSE

#OR

dds$condition <- factor(dds$condition, levels = c("untreated","treated"))

#OR

res <- results(dds, name="condition_treated_vs_untreated")
res <- results(dds, contrast=c("condition","treated","untreated"))

#Is it possible or how i can i translate this to doing DEseq2 on RECOUNT3 dataset?


# include your problematic code here with any corresponding output 
# please also include the results of running the following in an R session 

sessionInfo( )

Technically (in terms of "the code") yes you could do that, but since these are independent datasets there is a batch effect nested with the condition you test (batch1=cancer, batch2=normal) that you cannot correct, so it's a largely pointless analysis since you cannot discriminate between technical batch DEGs and real ones. This (combining TCGA and GTEx) has been asked many times before in several fora.