User: moldach

gravatar for moldach
moldach10
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New User
Location:
Canada/Montreal/Douglas Mental Health Institute
Website:
https://www.moldach.gi...
Twitter:
@MattOldach
Last seen:
1 month, 3 weeks ago
Joined:
3 years, 11 months ago
Email:
m******@ucalgary.ca

Posts by moldach

<prev • 19 results • page 2 of 2 • next >
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Using Human Protein Atlas annotations with pRoloc to interpretate subcellular location
... As my understanding the package pRoloc allows one to study the localisation of protein inside cells , using relative quantitation of known organelle residents, termed organelle markers. In the the vignette it uses `tan2009r1` data of markers that have been obtained by mining the pRolocdata datasets ...
annotation subcellular location proloc written 18 months ago by moldach10 • updated 18 months ago by Laurent Gatto1.2k
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Comment: C: Getting data into (and out of) the MSnSet object
... Thank you very much, exprs(res) <- round(exprs(res) * 1000) appears to work although I'm not exactly sure why? To be clear my data is normalized spectral counts (i.e. NSAF) prior to multiplication by 1000 and rounding. Is that the correct data format to be inputting? ...
written 19 months ago by moldach10
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Answer: A: Getting data into (and out of) the MSnSet object
... So the example from the msmsTests vignette for how to do differential expression analysis with edgeR goes like this: ## Example library(msmsTests) data(msms.dataset) e <- pp.msms.data(msms.dataset) e null.f <- "y~batch" alt.f <- "y~treat+batch" div <- apply(exprs(e),2,sum) res <- ms ...
written 19 months ago by moldach10
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Comment: C: Getting data into (and out of) the MSnSet object
... Hello and thank you for trying to help me Laurent. I'll put this into two comments for clarity. One thing I wanted to know was how to actually inspect the sample data provided in the pRoloc data set. I'll use hyperLOPIT-SIData-ms3-rep12-intersect.csv since this is what you showed above. I figured ...
written 19 months ago by moldach10
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Getting data into (and out of) the MSnSet object
... I would like to use the msmsTests package for differential expression analysis of proteins (spectral counts); however, the vignette only covers working with a MSnSet class and not how to get your data into that class. While the pRoloc vignette does mention how to convert csv files to the R data cla ...
proteomics msnbase msnset readmsnset msmstests written 19 months ago by moldach10
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Comment: C: Bioconductor vignette on Time course experiments only describes how to plot the
... Thank you very much James for your well written and well described answer. I don't have much computational support in my lab so figuring these things out can often be challenging - even with Google. I wracked my brain for nearly two weeks on your "homework" but to no avail. I thought I may be able ...
written 3.9 years ago by moldach10
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DESeq2 design issues - specifically understanding contrasts & interactions from page 23-25 of the DESeq2 manual
... Hello, I've read pages (23-25) of the DESeq2 manual many, many times yet I still need help interpreting the language. My PI read it as well and admitted "it's not his language" so I could really use some feedback right now. My model design looks like this: 4 time points in a month "lunar" (3Q, NM ...
deseq2 design and contrast matrix interactions contrast written 3.9 years ago by moldach10 • updated 3.9 years ago by Michael Love24k
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Answer: A: Bioconductor vignette on Time course experiments only describes how to plot the
... I'm still not understanding something very basic here.   topGene <- rownames(res)[which.min(res$padj)] plotCounts(dds, gene=topGene, intgroup=c("dex")   The code above creates a plot with a figure title saying "isogroup3584" - great! But that is only for the lowest p-value. Let's say instead ...
written 3.9 years ago by moldach10
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Bioconductor vignette on Time course experiments only describes how to plot the the gene with the smallest p-value. How can I plot specific genes of interest instead?
... The Bioconductor website offers an excellent RNA-Seq workflow vignette on Time-Course experiments however the ggplot2 only selects the gene with the smallest p-value, using the which.min() function:   data <- plotCounts(ddsTC, which.min(resTC$padj), intgroup=c("minute","stra ...
timecourse deseq2 time course rna-seq ggplot2 written 3.9 years ago by moldach10

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