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  • DESeq2 merged vs unmerged replicates

    Hi,

    I am currently analyzing a RNASeq experiments with 2 conditions. Each condition has several biological replicates and each replicate was sequenced multiple times (on different lanes and even flowcells). For each sub-replicate I have a separate fastq file.

    Control 1-1 Treatment 1-1
    Control 1-2 Treatment 1-2
    Control 1-3 Treatment 1-3
    Control 2-1 Treatment 2-1
    Control 2-2 Treatment 2-2
    Control 2-3 Treatment 2-3
    ...

    I performed now 2 analyses:
    1) Fastq -> STAR -> htseq count -> DESeq2
    2) Fastq -> Merge Fastqs of each replicate (1-1+1-2+1-3) -> STAR -> htseq count -> DESeq2

    I checked the count files and the individual counts of the replicates sum up to the merged count file.

    However, when I run now DESeq2 on the different count-data-sets I get different results (most notably the adj p-value).

    Not merged:
    Code:
                        baseMean log2FoldChange      lfcSE      stat        pvalue         padj
                       <numeric>      <numeric>  <numeric> <numeric>     <numeric>    <numeric>
    ENSG00000143369.10 479.26267      6.1618396 0.28753411  21.42994 7.026598e-102 2.636520e-97
    ENSG00000135250.12 381.34094      0.7005228 0.03782914  18.51807  1.476331e-76 2.769745e-72
    ENSG00000163898.5   62.74118      5.4375752 0.30318159  17.93504  6.281376e-72 7.856327e-68
    ENSG00000154269.10  65.19322      3.9433545 0.23587129  16.71825  9.651700e-63 9.053777e-59
    ENSG00000108821.9  306.78844      3.0304242 0.18264854  16.59156  8.020919e-62 6.019218e-58
    Merged:
    Code:
                         baseMean log2FoldChange     lfcSE      stat       pvalue         padj
                        <numeric>      <numeric> <numeric> <numeric>    <numeric>    <numeric>
    ENSG00000077327.11   63.88176     -3.1465321 0.5082833 -6.190509 5.997039e-10 1.553113e-05
    ENSG00000222022.1    13.70911      3.2297638 0.5455883  5.919782 3.223688e-09 4.174354e-05
    ENSG00000135250.12 3787.92187      0.7295915 0.1324829  5.507063 3.648689e-08 3.149791e-04
    ENSG00000108821.9  2925.22227      2.4831871 0.4592653  5.406869 6.413598e-08 4.152484e-04
    ENSG00000110427.10   74.67557      2.7264235 0.5144769  5.299409 1.161784e-07 6.017577e-04

    Could you please tell me if that is expected?
    Which approach should I use?

    Thanks for you help,
    Stephan

  • #2
    The difference is because DESeq2 thinks your technical replicates are biological replicates. If you really want to include them then the best you can do is to make a factor for the flow cell. I have yet to see an instance in the last few years where there's a lane batch effect (other than getting fewer reads...but that's not a batch effect). In reality, you might just do a PCA plot and if there's no real batch effect then go with the merged results.

    Comment


    • #3
      Thanks for the explanation.

      In my case, I'll go for the merged files, correct?

      Thanks,
      Stephan

      Comment


      • #4
        Correct

        Ignore me: this message is too short otherwise.

        Comment

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