Can I use DESeq2 for special assays
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@fereshteh-15803
Last seen 7 weeks ago
United Kingdom

Hi,

I have digital raw read counts of . Whatever I am googling I am not finding anybody used DESeq2 for differenial expresseion in this assay. I have done Differential expression with DESeq2 though. In this assay the expression levels of genes are assessed. Do you thing I can use DESeq2 for differential expression in this assay?

People in this publication used DESeq2 for assay https://www.htgmolecular.com/assets/htg/publications/2018_Myers_MicroRNA_Biomarkers_for_Parkinsons.pdf

Although this is on whole transcriptom on miRNAs rather than targeted sequencing

Thank you for any information

Targetedsequencing DESeq2 • 676 views
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@mikelove
Last seen 1 day ago
United States

I’ve used DESeq2 with Nanostring data of 150 and 400 genes panels for example. The model works fine, but the critical piece is the library size correction. We used housekeeping probes to correct for library size.

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Thanks a lot

In my digital raw read counts I have both negative, positive probes and house keeping genes as below

Probe Set   ESOBP                       ESOBP
Well    A1  A10 A11 A12 A2  A3  A4
Total Counts    2966772 3675646 5654645 120022  1895274 2977577 3156411
NEG_CTRL_ANT1   18  1   0   2   0   37  23
NEG_CTRL_ANT2   51  3   0   0   3   43  46
NEG_CTRL_ANT3   34  0   2   0   0   25  48
NEG_CTRL_ANT4   33  3   0   0   2   40  26
POS_CTRL_POS1   8311    315 1083    58  460 933 715
POS_CTRL_POS2   6291    267 869 50  367 780 574
POS_CTRL_POS3   4613    171 667 33  287 613 497
POS_CTRL_POS4   6504    266 846 42  327 774 581
ACTB    12370   18199   29477   800 8502    15629   13216
ATP5F1  716 1980    1751    28  679 1039    899
DDX5    7950    14671   12991   409 8006    8063    14763
EEF1G   6028    27192   26270   383 10279   15727   13000
GAPDH   49696   43011   123175  1553    33956   40181   49591
NCL 5432    11972   15514   251 10268   8243    9375
OAZ1    5669    6832    8674    240 3458    4078    5518
PPIA    713 4079    1693    37  748 1111    1258

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I use housekeeping in my case and made MA plots to assess if the normalization was appropriate. It’s not easy to describe in general the various ways to assess the normalization but is somewhat specific to the experiment and the known biology and known technical factors.

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How can you correct for library size using HK genes? Is there any way to specify that in the DESeq function?

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Run estimateSizeFactors() with controlGenes before running DESeq().

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