Hello everyone

I am have transcript abundance data from salmon for 24 samples. I am interested in the differential transcript usgae (DTU). I am following https://bioconductor.org/packages/release/workflows/vignettes/rnaseqDTU/inst/doc/rnaseqDTU.html#salmon-quantification workflow.

library(rnaseqDTU)


samps <- read.table(file="treated_samp", header = TRUE)

names(samps)  <- c("sample_id", "condition") 
head(samps)


samps$condition <- factor(samps$condition)
table(samps$condition)

files <- file.path("/home/test/Salmon/treated", samps$sample_id, "quant.sf")
names(files) <- samps$sample_id


library(tximport)
txi <- tximport(files, type="salmon", txOut=TRUE,
                countsFromAbundance="scaledTPM")
cts <- txi$counts
cts <- cts[rowSums(cts) > 0,]

range(colSums(cts)/1e6)

library(tidyverse)

dir <- "/home/test/"

tx2gene <- read_table(file.path(dir, "salmon_tx2gene.tsv"))

txdf <- tx2gene[,c(1:2)]

tab <- table(txdf$GENEID)


txdf$ntx <- tab[match(txdf$GENEID, names(tab))]



all(rownames(cts) %in% txdf$TXTname )

txdf <- txdf[match(rownames(cts),txdf$TXTname),]
all(rownames(cts) == txdf$TXTname)


txdf$TXNAME <- txdf$TXTname

counts <- data.frame(gene_id=txdf$GENEID,
                     feature_id=txdf$TXNAME,
                     cts)


library(DRIMSeq)

labels  <- colnames(counts) 

samps$sample_id <- labels[3:14]

d <- dmDSdata(counts=counts, samples=samps)

d


n <- 12

n.small <- 6

d <- dmFilter(d,
              min_samps_feature_expr=n.small, min_feature_expr=7,
              min_samps_feature_prop=n.small, min_feature_prop=0.1,
              min_samps_gene_expr=n, min_gene_expr=10)
d



library(DEXSeq)
sample.data <- DRIMSeq::samples(d)
count.data <- round(as.matrix(counts(d)[,-c(1:2)]))
dxd <- DEXSeqDataSet(countData=count.data,
                     sampleData=sample.data,
                     design=~sample + exon + condition:exon,
                     featureID=counts(d)$feature_id,
                     groupID=counts(d)$gene_id)

system.time({
  dxd <- estimateSizeFactors(dxd)
  dxd <- estimateDispersions(dxd, quiet=TRUE)
  dxd <- testForDEU(dxd, reducedModel=~sample + exon)
})


dxr <- DEXSeqResults(dxd, independentFiltering=FALSE)
qval <- perGeneQValue(dxr)
dxr.g <- data.frame(gene=names(qval),qval)

columns <- c("featureID","groupID","pvalue")
dxr <- as.data.frame(dxr[,columns])
head(dxr)


############# stageR following DRIMSeq


strp <- function(x) substr(x,1,15)

pConfirmation <- matrix(dxr$pvalue,ncol=1)
dimnames(pConfirmation) <- list(strp(dxr$featureID),"transcript")

pScreen <- qval

names(pScreen) <- strp(names(pScreen))

tx2gene <- as.data.frame(dxr[,c("featureID", "groupID")])
for (i in 1:2) tx2gene[,i] <- strp(tx2gene[,i])


stageRObj <- stageRTx(pScreen=pScreen, pConfirmation=pConfirmation,
                      pScreenAdjusted=FALSE, tx2gene=tx2gene)

Until this step of analysis, everything works fine. I am getting error at the following step :

stageRObj <- stageWiseAdjustment(stageRObj, method="dtu", alpha=0.05)

**Error in `[<-`(`*tmp*`, idCon, 1, value = unlist(txLevelAdjustments)) : 
  subscript out of bounds**

I tried different alpha values, but every time it gives me error.

I would appreciate all the suggestions.