Hi guys,

I'm relatively new to any type of analytics work and Rstudio. However, when inputting my TCGA data and doing all of the basic steps, my volcano plot and log2foldchange values seem to all be the opposite of what was expected. I understand perhaps this could just be the results of the data I have for my study, however I feel uncertain about it since every significant gene I am checking has previous known (without 100% certainty) logFC opposite to my study. I have attached the code below just to ask if it seems I have messed up my parameters or anything of the sorts. Much appreciated.

Code should be placed in three backticks as shown below

annotables_grch38 <- read_csv("annotables_grch38.csv")



## File ID to TCGA ID ##
# file_list.csv contains UUIDs
PatientEnsemblID<-read.csv("file_list.csv",header=FALSE)
colnames(PatientEnsemblID)<-"file_id" #provides a column header -> file_id

for (file in PatientEnsemblID){
  print(file)
  barcode<-UUIDtoBarcode(file, from_type = "file_id")
}

PatientIDSubtypeStatus<-read.csv("colDataTCGA.csv") #reading in colDataTCGA 

colnames(barcode) <- c("UUIG", "TCGA")

TCGA_raw_count_matrix <- read.csv("TCGA_raw_count_matrix.csv")

TCGA_CDR_SupplementalTableS1 <- read_excel("TCGA-CDR-SupplementalTableS1.xlsx")

colnames(barcode) <-c("file_id", "ID")

MergedByFileIDandPatientID <- left_join(barcode, PatientIDSubtypeStatus, by = "ID") 

MergedByFileIDandPatientID$bcr_patient_barcode = substr(MergedByFileIDandPatientID$ID, 1, 12)


PatientBarcodes <- t(MergedByFileIDandPatientID$bcr_patient_barcode)

colnames(TCGA_raw_count_matrix)
colnames(TCGA_raw_count_matrix) <- c("ID", patient)

BarcodeMerged <- left_join(barcode, MergedByFileIDandPatientID, by = "ID") 


BarcodeMerged$bcr_patient_barcode = substr(BarcodeMerged$ID, 1, 12)


capFirst <- function(s) {
  paste(toupper(substring(s, 1, 1)), substring(s, 2), sep = "")
}

BarcodeMerged$Subtype <- capFirst(BarcodeMerged$Subtype)

FilterForNeed <- filter(BarcodeMerged, Subtype == "Basal")

MetaDataFiltered <- select(FilterForNeed, bcr_patient_barcode, TP53)
MetaDataFiltered <- data.frame(FilterForNeed[, c("bcr_patient_barcode", "TP53")])

TCGAcorrelatingPatientBarcode <- TCGA_raw_count_matrix[, c("ID", MetaDataFiltered$bcr_patient_barcode)]


dfForMetaDataFiltered <- as.data.frame(MetaDataFiltered)

colnames(dfForMetaDataFiltered) <- c("Patient", "TP53")

rownames(TCGAcorrelatingPatientBarcode) <- TCGAcorrelatingPatientBarcode[,1]
TCGAcorrelatingPatientBarcode <- TCGAcorrelatingPatientBarcode[,-1]


ddsChanged <- DESeqDataSetFromMatrix(countData = TCGAcorrelatingPatientBarcode,
                                     colData = dfForMetaDataFiltered,
                                     design= ~ TP53 )

results

ddsChanged$TP53 <- factor(ddsChanged$TP53, levels = c("WT","MUT"))

dim(ddsChanged)
dim(ddsChanged[rowSums(counts(ddsChanged) >=1 ) >= 50])
ddsChanged <- ddsChanged[rowSums(counts(ddsChanged) >=1 ) >= 50]


vsdChanged <- vst(ddsChanged, blind=FALSE)

colnames(vsdChanged)
plotPCA(vsdChanged, intgroup=c("TP53"))
plotPCA(vsdChanged, intgroup=c("TP53")) +
  ggtitle("Basal TP53 - WT (29) vs MUT (142)")


ddsChanged <- DESeq(ddsChanged)
resultsNames(ddsChanged) 


MUTvsWTChanged <-results(ddsChanged, tidy=TRUE, contrast=c("TP53","MUT","WT"), independentFiltering = TRUE , alpha = 0.05)
MUTvsWTChanged <- as_tibble(MUTvsWTChanged)

Many thanks

Hello Mark, can you check if the levels of the dds are properly re-leveled? "WT" should be the reference in your dds, By reading this guide: "using relevel, just specifying the reference level:"

dds$condition <- relevel(dds$condition, ref = "WT")

If that helps you remember to vote the answer!