## User: Pietro

Pietro20
Reputation:
20
Status:
New User
Location:
Last seen:
2 months ago
Joined:
2 years, 3 months ago
Email:
d*************@gmail.com

#### Posts by Pietro

<prev • 8 results • page 1 of 1 • next >
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... Thanks Aaron, It's amazing how much we learn from guys like you. Still all FDR == 1, though. Here is what I meant... poor design? ![PCA][1] [1]: http://i63.tinypic.com/2w3bbpt.jpg ...
written 4 months ago by Pietro20
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... Interesting, thank you Aaron. Unfortunately I get no significant DE genes, probably because of the high variability of the cell lines. ...
written 5 months ago by Pietro20
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... Dear users, I am struggling to understand if my design is correct. I found edgeR section 3.3.1 similar to my situation but I am not that confident. Here is my experimental design: samples_table sampleId cellLine treatment time IC s1 a vehicle 0 S s2 ...
written 5 months ago by Pietro20 • updated 5 months ago by Aaron Lun24k
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... Hi Robert Thanks for the answer. I know very well the **GSVA** package, I use it everyday for the same purpose. My goal was trying to do the same with the **singscore** package and compare the results to see how the latter performs. Thanks anyway Pietro ...
written 5 months ago by Pietro20
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... Hello everyone Regarding the package [**singscore**][1], in particular the function simpleScore, that allows to score a gene expression dataset based on one or two gene sets, I was wondering if the signature scores from different gene sets are comparable. Say I have 4 gene sets that I use to cla ...
written 5 months ago by Pietro20 • updated 5 months ago by Robert Castelo2.3k
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... Regarding the approach to classify tumor samples to subtypes based on different gene sets with gene expression data, my question is: what is the significance of the approach when not all the genes of the gene sets are found in the samples? I believe that it may affect significantly the results, but ...
written 7 months ago by Pietro20
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... Thanks a lot, you were very clear! Can you briefly explain to humans like me what's the difference between design <- model.matrix(~Time, data=targets) # ​and design <- model.matrix(~factor(Time), data=targets) ? What would be the equivalent commands to do this in DESeq2? Thanks again ...
written 2.3 years ago by Pietro20
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... Dear all, I am working with a RNASeq data from an Arabidopsis experiment. The plants have been subjected to nitric oxide treatment for 3 hours and for 8 hours. I would like to find differentialy modulated genes not only in the classic between 2 comparison but also at any time in one test, following ...
written 2.3 years ago by Pietro20 • updated 2.3 years ago by londonflavido0

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