Hi, I have experienced very good results with DESeq2 for my RNASeq analysis. As far as I understand, it is a tool that normalise our data from sequencing to make them comparable. I have a new project implicating proteins counts. I have couple of data sets. For each sample we have: rows with proteins names (instead of genes), with their respective counts. My goal is again to make a differential expression between treated groups versus controls. I wonder if I can use DESeq2 to do a differential expression for proteins? Or if the correcting factor that is used by DESeq2 to correct counts for RNASeq is specific to DNA sequencing and it is not applicable to proteins? Is there a tool that do the exact same thing as DESeq2 but for proteins? Thank you very much for your help and time, Best regards and happy new year! Julie Cardin Bioinforamatician IRCM
[Bioc-devel] differential expression tools for proteins
5 messages · Cardin Julie, Diego Morais, Wolfgang Huber +1 more
Hi Cardin, this package does not do the same as DESeq2, http://bioconductor.org/packages/3.7/bioc/vignettes/transcriptogramer/inst/doc/transcriptogramer.html, but you can use it to do a differential expression for proteins (case x control). 2018-01-06 14:45 GMT-03:00 Cardin Julie via Bioc-devel < bioc-devel at r-project.org>:
Hi,
I have experienced very good results with DESeq2 for my RNASeq
analysis. As far as I understand, it is a tool that normalise our data from
sequencing to make them comparable.
I have a new project implicating proteins counts.
I have couple of data sets. For each sample we have:
rows with proteins names (instead of genes), with their respective counts.
My goal is again to make a differential expression between treated groups
versus controls.
I wonder if I can use DESeq2 to do a differential expression for proteins?
Or if the correcting factor that is used by DESeq2 to correct counts for
RNASeq is specific to DNA sequencing and it is not applicable to proteins?
Is there a tool that do the exact same thing as DESeq2 but for proteins?
Thank you very much for your help and time,
Best regards and happy new year!
Julie Cardin
Bioinforamatician
IRCM
[[alternative HTML version deleted]]
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Atenciosamente, Diego Arthur de Azevedo Morais [[alternative HTML version deleted]]
Dear Julie Thank you for your question. It would however be more appropriate for the support forum, not for the developer mailing list. Would you mind moving it there, perhaps also the responses so far? There is no "in-principle" reason why DESeq2 shouldn't produce useful results also for count data from technologies that are not DNA-sequencing based. It's error model (Gamma-Poisson, GP) is quite generic. As always, you should do model fit diagnostics though, to see whether the residuals for each protein across replicates and conditions (after fitting the GLM) are reasonably consistent with the GP, in particular, that they look unimodal. One issue to check is also whether the normalization (size factors) is appropriate. There is another bit of irony afaIu: If you have enough replicates (or: degrees of freedom) that you can actually "see" deviations from the GP assumption (i.e. >=dozens), then you probably don't need a parametric method, and could switch to something non-parametric. Kind regards Wolfgang 6.1.18 18:45, Cardin Julie via Bioc-devel scripsit:
Hi,
I have experienced very good results with DESeq2 for my RNASeq analysis. As far as I understand, it is a tool that normalise our data from sequencing to make them comparable.
I have a new project implicating proteins counts.
I have couple of data sets. For each sample we have:
rows with proteins names (instead of genes), with their respective counts.
My goal is again to make a differential expression between treated groups versus controls.
I wonder if I can use DESeq2 to do a differential expression for proteins?
Or if the correcting factor that is used by DESeq2 to correct counts for RNASeq is specific to DNA sequencing and it is not applicable to proteins?
Is there a tool that do the exact same thing as DESeq2 but for proteins?
Thank you very much for your help and time,
Best regards and happy new year!
Julie Cardin
Bioinforamatician
IRCM
[[alternative HTML version deleted]]
_______________________________________________ Bioc-devel at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/bioc-devel
With thanks in advance- Wolfgang ------- Wolfgang Huber Principal Investigator, EMBL Senior Scientist European Molecular Biology Laboratory (EMBL) Heidelberg, Germany wolfgang.huber at embl.de http://www.huber.embl.de
7.1.18 12:46, Wolfgang Huber scripsit:
Thank you for your question. It would however be more appropriate for the support forum, not for the developer mailing list. Would you mind moving it there, perhaps also the responses so far?
I just saw you posted on the forum, after browsing it. I had searched for your name using the "search" function of the forum webpage before sending the previous, but that did not turn up this post. Wouldn't it be great if our search box worked better? Or would just convert the search into an URL like https://www.google.com/search?q=Cardin+site%3Asupport.bioconductor.org&sort=date Wolfgang
On 01/07/2018 08:13 AM, Wolfgang Huber wrote:
7.1.18 12:46, Wolfgang Huber scripsit:
Thank you for your question. It would however be more appropriate for the support forum, not for the developer mailing list. Would you mind moving it there, perhaps also the responses so far?
I just saw you posted on the forum, after browsing it. I had searched for your name using the "search" function of the forum webpage before sending the previous, but that did not turn up this post. Wouldn't it be great if our search box worked better? Or would just convert the search into an URL like https://www.google.com/search?q=Cardin+site%3Asupport.bioconductor.org&sort=date
use the 'Users' and 'Tags' links at the top right to navigate users and tags. Poor search on the support site is a long-standing and well-known issue; some reasons (are they still valid?) for not simply using google are at https://github.com/Bioconductor/support.bioconductor.org/issues/4#issuecomment-56036398 where one can also access the code and propose pull requests. Martin
Wolfgang
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