Hi,
I counted my reads using featurecounts, now i was going to normalize them by DEseq2 package but I don't know what happened
> library("DESeq2")
> ddsSE <- DESeqDataSet(se, design = ~ cell + dex)
Error in assayNames(se) :
error in evaluating the argument 'x' in selecting a method for function 'assayNames': Error: object 'se' not found
> dds <- DESeqDataSetFromMatrix(countData = countData,
+ colData = colData,
+ design = ~ condition)
Error in as.matrix(countData) :
error in evaluating the argument 'x' in selecting a method for function 'as.matrix': Error: object 'countData' not found
> directory <- "/usr/data/nfs6/izadi/microarray/subread-1.4.6-p5-source/summary.txt/"
> dds <- DESeqDataSetFromMatrix(countData = countData,
+ colData = colData,
+ design = ~ condition)
Error in as.matrix(countData) :
error in evaluating the argument 'x' in selecting a method for function 'as.matrix': Error: object 'countData' not found
Please someone tell me what can I do
3 answers
Error: object 'se' not found
What do you think that means? You should be able to figure it out from the error message.
•
written
by
Devon Ryan
If you're an academic/ researcher, you need to take the time to learn R if you want to progress in Bioinformatics. Either you take some time learning the skills yourself, or you speak to your supervisor / boss and ask if there are any bioinformaticians within your facility you could consult with. Option C is that you ask your supervisor/ boss to send you on an R course. You can't just post every single error that you get and expect everyone within this community to figure out your problems for you. Sorry if that sounds harsh - but you need to be practical in filling the gaps in your knowledge!
•
written
by
andrew.j.skelton73
"se" should be your data
You can read in the DESeq2 vignette you need to provide to this package a data.frame (a sort of matrix) containing a list of genes names as row names, and the counts you get after mapping as columns whose col names are set with the names of all the conditions you use
You can do that with R, but you need to know some easy and basic knowledge of R to do so.
I can recommend the following
Tu run the R package
swirl()to learn some basics of R. Just install the package, load the library and runswirl(). And then just follow the instructions..To use excel to handle the data to format them in the way that DESeq is expecting to receive. I insist.. as rownames you need to provide the gene names, and so on, so still is likely that some handling need to be done with R
And stick to R. If you are using bioinformatics, you need to have some basic knowledge of it
•
written
by
Antonio R. Franco
Thank you Antonio,
This is few rows of my featurecounts output
Geneid accepted018347_hits.bam accepted019035_hits.bam acceptedSRR074122_hits.bam acceptedSRR074123_hits.bam acceptedSRR074123_hits.bam acceptedSRR314813_hits.bam acceptedSRR314814_hits.bam acceptedSRR314815_hits.bam acceptedSRR331224_hits.bam acceptedSRR346552_hits.bam acceptedSRR346553_hits.bam acceptedSRR390313_hits.bam
AT1G01010 31 37 4 3 3 57 685 138 267 114 215 9
AT1G01020 153 211 19 8 8 132 192 130 89 233 260 14
AT1G01030 10 13 0 1 1 80 13 78 6 95 89 2
AT1G01040 88 106 3 0 0 647 776 1036 442 865 963 30
I need to normalize this file until Thursday, but really I got confused...
Take a look to pages 5 and 6 of this document
How have loaded your data?
The DESeqDataSet() function is expecting data already formatted as a SummarizedExperiment format, and your data does not have this format. You must follow section 1.2.3 "Count matrix input" that will let you enter your data. You must also provide with another data.frame containing the conditions. See the vignette for the details
You just after loading the library and after creating both dataframes (counts and conditions)..
dds <- DESeqDataSetFromMatrix(countData = your_featurecounts_output_file, colData = colData, design = ~ condition)
In page 5 and 6 i typed the codes
> library("DESeq2")
> ddsSE <- DESeqDataSet(se, design = ~ cell + dex)
> ddsSE
class: DESeqDataSet
dim: 64102 8
exptData(1): ''
assays(1): counts
rownames(64102): ENSG00000000003 ENSG00000000005 ... LRG_98
LRG_99
rowRanges metadata column names(0):
colnames(8): SRR1039508 SRR1039509 ... SRR1039520 SRR1039521
colData names(9): SampleName cell ... Sample BioSample
But is this is not my data
It is sort of confusing
After running
ddsSE <- DESeqDataSet(se, design = ~ cell + dex)
the first time, you got an error
Now you run the same code, and no error whatsoever.. And I don't know why..
DeSeqDataSet is used when your data is formatted as a SummarizeExperiment coming from another program or package
And you must use DESeqDataSetFromMatrix() when you have a matrix with gene names and counts. In this case, another data.frame is required that describe the conditions of your experiment
I don't know where the "se" data comes from and how you got it
•
written
by
Antonio R. Franco
It seems that you got your data already. Keep going with the analysis
•
written
by
Antonio R. Franco
see pag 17...
Ok I see
It seems that you have your data.frame with counts already done
Now you need to create a design condition. Here is a copy of the code I use in my own DESeq2
design <- data.frame(mutant=c("704","704","4249","4249","8987","8987"), condition= c("N","NA","N","NA","N","NA"))
rownames(design) <- c("N704","NA704","N4249","NA4249","N8987","NA8987") # We name rows
head(diseno)
See the c(data, bla bla..) ? Mutants are a set of three mutants in my case. conditions indicate that they were treated in two different ways. There are infinite ways of designing your experiments
You need to create a data.frame with your conditions and or treatment in a similar way
Once you have both, you ca import your data into DESeq
•
written
by
Antonio R. Franco
Thank you so much for your patience...
As I told I only have a file containing the reads count by featurecounts in txt format as I pasted above...
Then do I have data frame or I should do perform something to create data frame?
I have 61 samples collected from various RNA-seq experiments with various condition
I named the sample by the SSR accession for example SSR047183 and not like your case defined by treatment or control
Anyway you thought me to preparing the condition design (I have not tried yet) but what can I do for data frame?
Send me your e-mail. I will help you in private. We will post here the solution afterwards. Mine es arfranco at uco.es
•
written
by
Antonio R. Franco
Is there any reason why you are creating DESeq2 object using 2 methods at the same time? Were you trying different methods to create DESeqDataSets? (code copy/pasted from OP)
1) Creating DESeqDataSet from sumarized experiment
> ddsSE <- DESeqDataSet(se, design = ~ cell + dex)
2) Creating DESeqDataSet from Matrix
> dds <- DESeqDataSetFromMatrix(countData = countData,
+ colData = colData,
+ design = ~ condition)
Log in to answer this question.
-
Error function vst in DESeq2
written by Larissa •
-
DiffBind count function error related with BiocParallel and IRanges
written by buffealo •
-
TCGA single dataset normalization
written by ruby4bioinfo •
-
DESeq2 saying that dimensions of count matrix and metadata don't agree, but they do agree
written by hippo •
-
DESeq2 problem "DESeqDataSetFromMatrix function"
written by ania.karwot •
-
Question: can not obtain DESeq2 results
written by zjxia •
-
Error: could not find function "DESeqDataSet" from DESeq2
written by imrankhanbioinfo •
-
DESeq2 and integers values
written by Morris_Chair
-
error in getting results from DESeq2
written by nazaninhoseinkhan
-
FeatureCounts from Galaxy to DESeq2 in RStudio
written by Newbieish •
