How to save the DEXSeq results
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Entering edit mode
Sara • 0
@95b4edca
Last seen 17 hours ago
Belgium

Hi,

after all the step of DEXSeq I wanted to save my results in a tsv, csv, ... but nothing helped me I also followed the other similar questions related to this issue but nothing helped. May you please kindly help how to save the results

results <- DEXSeqResults(dx)

> class(results)
[1] "DEXSeqResults"
attr(,"package")
[1] "DEXSeq"

> write.table(results, "dexseq.tsv", sep="\t", quote=F, row.names=F)
Error in write.table(results, "dexseq.tsv", sep = "\t", quote = F, row.names = F) : 
  unimplemented type 'list' in 'EncodeElement'

then I converted to dataframe, but still can't save the results:

df_results <- as.data.frame(results)

> write.table(df_results , "dexseq.tsv", sep="\t", quote=F, row.names=F)
Error in write.table(df_results, "dexseq.tsv", sep = "\t", quote = F,  : 
  unimplemented type 'list' in 'EncodeElement'

Then just tried to get the significant ones, but still, I can't save it:

dxr1.sig <- as.data.frame(results[results$padj < 0.1 & !is.na(results$padj),])

> write.table(dxr1.sig, "Results.tsv", quote=FALSE, sep="\t", dec=".")
Error in write.table(dxr1.sig, "Results.tsv", quote = FALSE, sep = "\t",  : 
  unimplemented type 'list' in 'EncodeElement'

Looking forward for solutions. Many thanks!

DEXSeq • 168 views
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3
Entering edit mode
@mikelove
Last seen 3 days ago
United States

If you look at the output here:

https://bioconductor.org/packages/release/bioc/vignettes/DEXSeq/inst/doc/DEXSeq.html#4_Testing_for_differential_exon_usage

You can see there are some columns that are different than the others, e.g. <GRanges>, <matrix>, and <list>.

You can instead select just the standard columns:

> d <- DataFrame(x = 1:10, y=letters[1:10])
> d$z <- as.list(1:10)
> d
DataFrame with 10 rows and 3 columns
           x           y      z
   <integer> <character> <list>
1          1           a      1
2          2           b      2
3          3           c      3
4          4           d      4
5          5           e      5
6          6           f      6
7          7           g      7
8          8           h      8
9          9           i      9
10        10           j     10
> d |> as_tibble() |> select_if(~is.character(.x) | is.numeric(.x))
# A tibble: 10 × 2
       x y
   <int> <chr>
 1     1 a
 2     2 b
 3     3 c
 4     4 d
 5     5 e
 6     6 f
 7     7 g
 8     8 h
 9     9 i
10    10 j

Another option would be to flatten the list column before removing the others (matrix/GRanges).

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