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NA values of count matrix in class DESeqDataSet

Dear all

Hi

I downloaded a data set in class "RangedSummarizedExperiment" from "https://jhubiostatistics.shinyapps.io/recount/". I want to find differential expression genes. My code is :

load("~/Downloads/rse_gene.Rdata")

class(rse_gene)

**[1] "RangedSummarizedExperiment"

attr(,"package")

[1] "SummarizedExperiment"**

data=colData(rse_gene)

names= names(colData(rse_gene))

write.table(data,file="colData.csv", col.names=names,sep="\t",row.names=FALSE)

data1=fread("~/Downloads/colData.txt")

colData(rse_gene) =DataFrame(data1)

colData(rse_gene)$disease.status = as.factor(colData(rse_gene)$disease.status)

dds <- DESeqDataSet(rse_gene, design = ~ disease.status)

**converting counts to integer mode Error in validObject(.Object) :

invalid class “DESeqDataSet” object: NA values are not allowed in the count matrix In addition: Warning message: In mde(x) : NAs introduced by coercion to integer range**

I use two solution for this problem but both of them were useless:

1- Keep only rows with non-zero counts:

rse_gene <- rse_gene[rowSums(assay(rse_gene)) != 0, ]

2- Replace the NA value by -9 :

countdata <- assay(rse_gene)

replace(countdata,countdata==0,-9)

coldata <- colData(rse_gene)

ddsMat <- DESeqDataSetFromMatrix(countData = countdata, colData = coldata, design = ~ disease.status)

I will be appreciate if any one can help me!!

rna-seq recount
• 12,537 views • link
written by maleknias • maleknias

Try this:

library(DESeq2)
load("rse_gene.Rdata")
ddsse=DESeqDataSet(rse_gene,design=~disease.status)

Btw, what is the accession number of the data?

• 0 views • link
written by cpad0112 cpad0112

2 answers

Your command using rowSums won't work. What I normally do is something like this:

test <- data.frame(c(1,2,3,4,5), c(1,2,3,4,5), c(1,NA,3,4,5), c(NA,NA,NA,4,5), c(1,2,3,4,5))
colnames(test) <- c("a","b","c","d","e")
test
a b  c  d e
1 1  1 NA 1
2 2 NA NA 2
3 3  3 NA 3
4 4  4  4 4
5 5  5  5 5

test[apply(test, 1, function(x) sum( is.na(x) ))==0,]
a b c d e
4 4 4 4 4
5 5 5 5 5

I originally used this way of filtering for removing transcripts that had zero counts across 5 or more samples, using something like this:

apply(test, 1, function(x) sum(x==0))<5
• 0 views • link
written by Kevin Blighe Kevin Blighe

Instead of 

test[apply(test, 1, function(x) sum( is.na(x) ))==0,]

you could use the built-in function complete.cases, e.g

test[complete.cases(test), ]
• 0 views • link
written by e.rempel e.rempel

Thanks e.rempel - I knew that the function existed but could not remember the name at the time of writing!

• 0 views • link
written by Kevin Blighe Kevin Blighe

Dear all

I used all your guide but unfortunately all of them have the last same error !!

first:

assay(rse_gene)=assay(rse_gene)[apply(assay(rse_gene), 1, function(x) sum( is.na(x) ))==0,]

dds <- DESeqDataSet(rse_gene, design = ~ disease.status)

second:

assay(rse_gene)=assay(rse_gene)[complete.cases(assay(rse_gene)),]

dds <- DESeqDataSet(rse_gene, design = ~ disease.status)

I will be appreciate if any one can help me!!

• 0 views • link
written by maleknias • maleknias

Try to remove the NA values before you run that function. I'm not sure that the code you have above is going to behave in the way that you expect.

I don't know why you need to use the assay() function before DESeqDataSet()

Can you not just remove NA values from your raw counts matrix before you do anything with DESeq?

• 0 views • link
written by Kevin Blighe Kevin Blighe 
> rse_gene <- data.frame(c(1,2,3,4,5), c(1,2,3,4,5), c(1,NA,3,4,5), c(NA,NA,NA,4,5), c(1,2,3,4,5))
> colnames(rse_gene) <- c("a","b","c","d","e")
> rse_gene[is.na(rse_gene))] <- 0
> rse_gene
  a b c d e
1 1 1 1 0 1
2 2 2 0 0 2
3 3 3 3 0 3
4 4 4 4 4 4
5 5 5 5 5 5
> dds <- DESeqDataSet(rse_gene, design = ~ disease.status)
• 0 views • link
written by ioannis • ioannis

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