Question: error while using edgeR( Negative counts not allowed)
1
gravatar for deeksha3696
2.0 years ago by
deeksha369610
deeksha369610 wrote:

I am doing an RNAseq analysis. (using edgeR) I am loading my data for differential analysis, my data is of normalized gene expression(FPKM). I am now just trying to make DEGList object but, it is showing "Negative counts not allowed".

I have removed all negative values from the data, it is still showing the error(( Negative counts not allowed).

Please suggest what should i do. thank you!!

Command:

dgeFull <- DGEList(y, group = sampleInfo$condition)
Error: Negative counts not allowed
edger rna-seq R • 2.3k views
ADD COMMENTlink modified 2.0 years ago by zx87549.9k • written 2.0 years ago by deeksha369610
5
gravatar for WouterDeCoster
2.0 years ago by
Belgium
WouterDeCoster45k wrote:

my data is of normalized gene expression(FPKM).

You need raw counts for edgeR. Don't use any normalization.

ADD COMMENTlink written 2.0 years ago by WouterDeCoster45k

thanks from where can i get the raw counts

ADD REPLYlink written 2.0 years ago by deeksha369610
1

Download the data from NCBI or directly from ENA ( Fast download of FASTQ files and metadata from the European Nucleotide Archive (ENA) ).

ADD REPLYlink modified 2.0 years ago • written 2.0 years ago by ATpoint45k

From where did you get the fpkm counts...?

We are bad at reading your mind so you'll have to elaborate.

ADD REPLYlink written 2.0 years ago by WouterDeCoster45k

I downloaded the fpkm values from NCBI GEO DATA SET

ADD REPLYlink written 2.0 years ago by deeksha369610
1

FPKM values are not suitable for statistics, this is a recurrent discussion. See also edgeR user's guide, end of 2.3 on page 12. You need raw read counts, if they don't provide them at GEO, you can redo the analysis: download fastq files -> align them to reference e.g. with STAR -> counts reads with e.g. featureCounts

ADD REPLYlink modified 2.0 years ago • written 2.0 years ago by Benn8.1k

While I don't completely agree that FPKM can't be used for any statistics (and I think it can be useful for visualization), it is true that you need raw counts for edgeR (and most RNA-Seq Bioconductor differential expression packages).

I also agree re-processing raw data can be frequently be helpful. Even if you end up with a similar result, you should understand the analysis process better and be more confident in your results :)

ADD REPLYlink written 2.0 years ago by Charles Warden8.0k

Please add a link to the dataset you are using. It may be necessary to download the reads and process those yourself.

ADD REPLYlink written 2.0 years ago by WouterDeCoster45k
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