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  • greigite
    Senior Member
    • Mar 2009
    • 145

    #1

    DESeq2: problem with variance stabilization

    I think I am probably missing something obvious here with DESeq2. I used to use DESeq frequently to normalize count data but somehow cannot get the same process to work in DESeq2. I am able to create a DESeqDataSet object and run analysis with the DESeq function without difficulty, but then can't retrieve a normalized matrix of counts from a DESeqDataSet object following variance stabilization. The problem seems to be that the entry "counts" in the "assays" slot disappears after running varianceStabilizingTransformation.

    Code:
    dds_blind=DESeqDataSetFromMatrix(countData=sample_otu_table,colData=BRR_env,formula(~1))
    
    dds_blind<-DESeq(dds_blind,fitType=c("parametric"))
    Results:
    Code:
    > dds_blind
    class: DESeqDataSet 
    dim: 70232 92 
    exptData(0):
    assays(1): counts
    rownames(70232): OTU_1 OTU_3 ... OTU_46831 OTU_34574
    rowData metadata column names(0):
    colnames(92): 35 52 ... 211 281
    colData names(5): collection_type block Zhao_name CGN crop
    > dds_blind<-DESeq(dds_blind,fitType=c("parametric"))
    estimating size factors
    estimating dispersions
    gene-wise dispersion estimates
    mean-dispersion relationship
    final dispersion estimates
    fitting model and testing
    > dds_blind
    class: DESeqDataSet 
    dim: 70232 92 
    exptData(0):
    assays(3): counts mu cooks
    rownames(70232): OTU_1 OTU_3 ... OTU_46831 OTU_34574
    rowData metadata column names(19): baseMean baseVar ... deviance maxCooks
    colnames(92): 35 52 ... 211 281
    colData names(6): collection_type block ... crop sizeFactor
    Now trying variance stabilization, note that "counts" vanishes from the assays slot after running the function:
    Code:
    > vsd<-varianceStabilizingTransformation(dds_blind,blind=TRUE)
    you had estimated gene-wise dispersions, removing these
    you had estimated fitted dispersions, removing these
    > vsd
    class: SummarizedExperiment 
    dim: 70232 92 
    exptData(0):
    assays(1): ''
    rownames(70232): OTU_1 OTU_3 ... OTU_46831 OTU_34574
    rowData metadata column names(23): baseMean baseVar ... dispGeneEstConv.1 dispFit
    colnames(92): 35 52 ... 211 281
    colData names(6): collection_type block ... crop sizeFactor
    > getVarianceStabilizedData(vsd)
    Error in (function (classes, fdef, mtable)  : 
      unable to find an inherited method for function ‘dispersionFunction’ for signature ‘"SummarizedExperiment"’
    > counts(vsd)
    Error in (function (classes, fdef, mtable)  : 
      unable to find an inherited method for function ‘counts’ for signature ‘"SummarizedExperiment"’
    Last edited by greigite; 02-17-2014, 07:15 PM.
  • dpryan
    Devon Ryan
    • Jul 2011
    • 3478

    #2
    Try
    Code:
    getVarianceStabilizedData(dds_blind)
    BTW, I don't think "SummarizedExperiment" objects have a "counts()" accessor.

    Comment

    • Michael Love
      Senior Member
      • Jul 2013
      • 333

      #3
      Yes,

      the normalized values are accessible with the assay() function for SummarizedExperiments

      Comment

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