DESEq2 error - 'DESeqDataSet' object superclass 'RectangularData' not defined in the environment of the object's class

Question

[susheelbhanu]

Hi all,

I've used DESeq2 many times before, but for some reason, running into the below issue

Error in validObject(.Object) :    invalid class “DESeqDataSet”
object: superclass "RectangularData" not defined in the environment of
the object's class

My code is as follows:

BiocManager::install("DESeq2") 

library(DESeq2)

kegg_mg <- read.delim(here("kegg",

"aaron_metaG_KEGG_counts_merged.txt"), 
                      header=TRUE) %>% as.matrix()
y_mg <- data.frame(row.names=c("GM1a", "GM1b", "GM1c", "GM4a", "GM4b",
 "GM4c"), 
                 condition=as.factor(c(rep("GM1",3), rep("GM4",3))))

 ddsMat_mg <-DESeqDataSetFromMatrix(countData = kegg_mg, colData =
 y_mg, design = ~ condition)

I've restarted Rstudio. Purged all the existing packages and did a clean re-install, and still the problem persists. My input file is a table with 6 columns and count values. Thank you for your help!

Answer 1

[Michael Love]

Class-related issues often result from invalid installations of Bioconductor, e.g. packages crossing from different Bioc releases. As the packages are built off of a common framework defining classes, conflicting versions often leads to errors like the above.

Can you run:

BiocManager::valid()

And see if you can spot any issues there?

Answer 2

[Kevin Blighe]

The problem can likely be solved by following these simple tips:

• kegg_mg should be a data-frame of integer values representing raw counts
• y_mg should be a data-frame of metadata, with character vectors encoded as factors (i.e. encoded categorically) - continuous vectors are also permitted
• This should be TRUE: nrow(y_mg) == ncol(kegg_mg)
• This should be TRUE: rownames(y_mg) == colnames(kegg_mg)

If you need further help, please show the output of:

str(kegg_mg)
str(y_mg)

Kevin

[lilyfan129]

Hi Keven, I had the same problem. I checked my countData with" is.integer(countData) " and the output is True. I think my data meets all the requirements you listed above. Could you help me with this? Thank you!

str(countData)
 num [1:23669, 1:42] 0 60 74 227 285 ...
 - attr(*, "dimnames")=List of 2
  ..$ : chr [1:23669] "ADH6" "SLC6A13" "FGD1" "MDM4" ...
  ..$ : chr [1:42] "R8202" "R9159" "R9160" "R9163" ...

the output of str(metadata)

str(meta)
 chr [1:42, 1:3] "-9/-9" "-9/-9" "-9/-9" "-9/-9" "wt" "wt" "wt" "w/-9" "-9/-9" "w/-9" ...
 - attr(*, "dimnames")=List of 2
  ..$ : chr [1:42] "R8202" "R9159" "R9160" "R9163" ...
  ..$ : chr [1:3] "Genot" "gender" "time"

[Kevin Blighe]

Hello, how about running class() and typeof() on these objects?

Can you also show the sequence of commands that you are running?

[lilyfan129]

Hi Keven,

I tried to read my data from the CSV files again. Here are my code and the outs. code:

# ge contains 6 sets of my data.
ge <- read.csv("/home/x/00-data/Rabbit/Raw.Normalized_Counts_All.Genes.All.Samples.csv")
names <- make.unique(ge$GeneName)
rownames(ge) <- names
ge <- ge[,-1]

# brush is my target data.
brush <- ge[ , grepl( ".3_Raw" , names( ge ) )]
colnames(brush) <- substr(colnames(brush ), 1, 5 )
tmp2 <- rowSums(brush)>1
brush <- brush[tmp2,]
brush <- brush[,-1]


## adjust the order of rownames
id <- c(colnames(brush))
id <- data.frame(id=id)

meta <- read.csv("/home/x/00-data/Rabbit/meta_rabbits.csv", header= T)
meta <- left_join(id, meta,by = "id")
rownames(meta) <- meta[,1]
meta <- meta[,-1]


library(DESeq2)
library(gplots)
dds <- DESeqDataSetFromMatrix(countData = brush, colData = meta, design= ~ Genot.)

Then I got the error message again.

str(brush)
'data.frame':   18384 obs. of  42 variables:
 $ R8202: int  0 60 74 227 285 225 2 3392 2748 2393 ...
 $ R9159: int  0 108 145 254 258 70 0 3616 2601 2301 ...
 $ R9160: int  0 197 136 239 140 121 0 3486 2709 2222 ...
 $ R9163: int  0 83 129 242 127 250 0 2648 2486 1684 ...
 $ R9166: int  0 289 153 213 178 424 1 4455 2817 2084 ...

....

str(meta)
'data.frame':   42 obs. of  5 variables:
 $ time  : chr  "Year old" "Wks_4" "Wks_4" "Wks_4" ...
 $ DOB   : chr  "7/6/2017" "5/22/2018" "5/22/2018" "5/22/2018" ...
 $ DOE   : chr  "8/30/2018" "6/18/2018" "6/18/2018" "6/18/2018" ...
 $ Genot.: chr  "-9/-9" "-9/-9" "-9/-9" "-9/-9" ...
 $ gender: chr  "M" "F" "M" "M" ...

class(brush)
[1] "data.frame"
 typeof(brush)
[1] "list"

class(meta)
[1] "data.frame"
typeof(meta)
[1] "list"

Do you have any suggestions? Thank you!

Li

[Kevin Blighe]

Please see the suggestion by Michael below