User: hesse.sebastian

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Posts by hesse.sebastian

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Selecting the background for GO enrichment analysis (proteomics)
... Im using clusterProfiler for GO enrichment of differentially expressed proteins from different groups. It appears that most suitable is to use as a background for enrichment all proteins that "potentially could be in the lift of the differentially expressed proteins". My issue is that I am not 100% ...
proteomics enrichment clusterprofiler go written 11 weeks ago by hesse.sebastian80 • updated 11 weeks ago by Jean-Karim Heriche20k
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Comment: C: Using clusterprofiler (or else) top look for enrichment of one specific GO term
... Great workaround, thanks! ...
written 3 months ago by hesse.sebastian80
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Using clusterprofiler (or else) top look for enrichment of one specific GO term
... In my set of differentially expressed proteins (derived from comparison of different genotypes to healthy) I would like to check if specific GO-terms are enriched (eg. if one set of proteins contains significantly more often the annotation for "membrane" = GO:0016020). Currently I am using clusterP ...
R bioconductor clusterprofiler enrichment written 3 months ago by hesse.sebastian80 • updated 3 months ago by jared.andrews072.7k
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Comment: C: PVCA message: boundary (singular) fit: see ?isSingular
... Is there something I could/should do about? What I noticed in this particular combination of samples (I am performing proteome analysis with different groups of patients agains a large healthy comparison group) is that "age" is a very strong variance influence. I suppose this has to do with the part ...
written 3 months ago by hesse.sebastian80
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PVCA message: boundary (singular) fit: see ?isSingular
... Running the pvcaBatchAssess from the pvca package I get the message: "boundary (singular) fit: see ?isSingular". Unfortunately I do not understand this message and also "?isSingular" doesnt help me much. Can you advice me on what to do? The function runs through though and I get a graphical output ...
R pvca written 3 months ago by hesse.sebastian80
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Comment: C: Interpretation of linear modelling quality test
... Thank you all for your inputs! I made more graphs/calculations and moved the question [here][1] [1]: https://support.bioconductor.org/p/118495/#118500 ...
written 4 months ago by hesse.sebastian80
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Answer: A: removeBatchEffect with or without log2 values
... As VOOM gave strange results that still showed heteroscedasticity I solved it now using log2 values and the LIMMA option `eBayes(fit2_object, trend = F, robust = T) ` Thank you all for your input! ...
written 4 months ago by hesse.sebastian80
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How to correctly correct for batch effects
... Working with a proteome dataset I would like to check and correct for batch effects. For batch effect detection I am using [PVCA][1], for batch effect correction LIMMAS [removeBatchEffect][2]. Data come from DIA proteome analysis, quantified using Biognosys Spectronaut 11, details can be found in ou ...
removebatcheffect R pvca limma written 4 months ago by hesse.sebastian80
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Comment: C: removeBatchEffect with or without log2 values
... Thanks a lot for your answer ivivek! I agree with all your points and actually follow them, only the one about doing the diff ex analysis with counts instead of log2 values is puzzling me. I am working with DIA derived quantitative proteome data. So far I always put log2 values into LIMMA for diff ...
written 4 months ago by hesse.sebastian80
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removeBatchEffect with or without log2 values
... Using LIMMA's removeBatchEffect and PVCA to check for batch influences before and after removal I just noticed that if I don't use log2 values the batch effect removal does not work in the sense that PVCA shows retained batch effects after removal. With log2 values all runs fine. Is this a general ...
removebatcheffect R limma written 4 months ago by hesse.sebastian80

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