[R] ERROR with Aggregate differentially expressed genes across all contrast results using DEVis/DESeq
jdnewm|| @end|ng |rom dcn@d@v|@@c@@u@
Wed Jun 29 22:06:27 CEST 2022
Well, the problem may in fact lie in your use of R somehow, but I don't use Bioconductor and do not intend to start. If you can make your example reproducible and post it using plain text then maybe someone here who does use Bioconductor will look closer at it.
On June 29, 2022 12:14:05 PM PDT, Ana Ruiz Manzano <aruizman2 using gmail.com> wrote:
>Thanks for replying! And sorry for the formatting, I actually read about it
>but sent the email before realizing.
>I previously posted this in the Bioconductor forum but then sent me to you.
>On Wed, Jun 29, 2022 at 14:08 Jeff Newmiller <jdnewmil using dcn.davis.ca.us>
>> This question should most likely have been asked in the Bioconductor
>> support forum.
>> For future reference, if you are looking for help with R rather than deep
>> details about using a non-CRAN package, do turn off HTML formatting in your
>> email software when you send to this list, as such formatting gets stripped
>> anyway and what is left is barely legible.
>> On June 29, 2022 9:05:11 AM PDT, Ana Ruiz Manzano <aruizman2 using gmail.com>
>> >I'm using DEVis for differential expression analysis. When I get to
>> running DESeq I get an error about "object of class �NULL� is not valid"
>> when I'm creating the aggregated data.
>> >running BiocManager::valid() returns  TRUE and restarting RStudio
>> didn't solve it either.
>> >#Run DESeq on my previously prepared DESeq2 object.
>> > dds <- DESeq(dds)
>> >#determine the contrasts we are interested in examining by using DESeq2's
>> results() function
>> > res.SAMPLE3.vs.C2 <- results(dds, contrast=c("condition_ppGpp",
>> "untreated_0mM", "treated_0.5mM"))
>> > res.SAMPLE4.vs.C2 <- results(dds, contrast=c("condition_ppGpp",
>> "untreated_0mM", "treated_1mM"))
>> > print(res.SAMPLE3.vs.C2)
>> >log2 fold change (MLE): condition_ppGpp untreated_0mM vs treated_0.5mM
>> >Wald test p-value: condition ppGpp untreated 0mM vs treated 0.5mM
>> >DataFrame with 3996 rows and 6 columns
>> > baseMean log2FoldChange lfcSE stat pvalue padj
>> > <numeric> <numeric> <numeric> <numeric> <numeric> <numeric>
>> >1 352.326 0.2830664 0.391703 0.7226560 0.4698913 0.6771991
>> >2 335.373 0.5624211 0.270855 2.0764617 0.0378513 0.1542207
>> >3 315.891 0.6081361 0.237291 2.5628297 0.0103823 0.0653239
>> >4 326.854 -0.0200133 0.275640 -0.0726069 0.9421189 0.9702167
>> >5 360.061 -0.6693134 0.317713 -2.1066623 0.0351469 0.1471803
>> >... ... ... ... ... ... ...
>> >3992 0.1194548 -3.02243 4.02648 -0.750639 0.45287 NA
>> >3993 0.0481303 0.00000 4.06264 0.000000 1.00000 NA
>> >3994 0.0481303 0.00000 4.06264 0.000000 1.00000 NA
>> >3995 0.0481303 0.00000 4.06264 0.000000 1.00000 NA
>> >3996 0.1218624 0.00000 4.06264 0.000000 1.00000 NA
>> >#Make a list of all of our contrasts.
>> > result_list <- list(res.SAMPLE3.vs.C2, res.SAMPLE4.vs.C2)
>> > print(result_list)
>> >#Aggregate differentially expressed genes across all contrast results.
>> > master_dataframe <- create_master_res(result_list,
>> filename="master_DE_list.txt", method="union", lfc_filter=TRUE)
>> >Error in (function (cl, name, valueClass) :
>> > assignment of an object of class �NULL� is not valid for @�allNames� in
>> an object of class �DESeqResMeta�; is(value, "character") is not TRUE
>> >I have tried to replace the NA data points in my data to zeros using the
>> is.na() <- 0 function, but then I get an error
>> >Error in create_master_res(result_list, filename = "master_DE_list.txt",
>> > create_master_res() requires list type object containing DESeq result
>> >Changing data.frame to list didn't hep either.
>> >What I am missing?
>> > [[alternative HTML version deleted]]
>> Sent from my phone. Please excuse my brevity.
Sent from my phone. Please excuse my brevity.
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