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Question: How to access normalized data in the NanoStringDiff package?
0
4 months ago by
casey.rimland100
University of Cambridge, National Institutes of Health, Chapel Hill School of Medicine
casey.rimland100 wrote:

I am trying to use NanoStringDiff for differential expression analysis of a nanostring data-set with 506 endogenous genes in the set. I was wondering how/if there is a way to output the normalized data that NanoStringDiff uses to run the differential expression LRT tests? I have been able to run the differential expression analyses correctly (I hope!), but now would like to know if there is a way to access the normalized data to use for PCA plots, heatmaps, etc? I tried assay(exprs) but it just gave me the raw counts. Thanks!

path<-paste(dir,"nanostring_R.csv",sep="/")
designs <- data.frame(group=c("WT_IL13", "WT_IL13", "WT_IL13", "WT_CTRL", "WT_CTRL", "WT_CTRL", "RA1_IL13", "RA1_IL13", "RA1_IL13", "RA1_CTRL", "RA1_CTRL", "RA1_CTRL"))

#Create a Nanostring dataset
nanostringdata <- createNanoStringSetFromCsv(path = path, header = TRUE, designs = designs)

#Run DE analysis
pheno=pData(nanostringdata)
group=pheno\$group
design.full=model.matrix(~0+group)
design.full

NanoStringData_Norm <- estNormalizationFactors(nanostringdata)

#Get Results for pairwise contrasts
result_WT <- glm.LRT(NanoStringData_Norm,design.full,contrast=c(0,0,-1,1))
modified 4 months ago by James W. MacDonald48k • written 4 months ago by casey.rimland100
1
4 months ago by
United States
James W. MacDonald48k wrote:

I don't think there is a direct accessor, but this is what is done to the data prior to fitting any model:

    c = positiveFactor(NanoStringData)
d = housekeepingFactor(NanoStringData)
k = c * d
lamda_i = negativeFactor(NanoStringData)
Y = exprs(NanoStringData)
Y_n = sweep(Y, 2, lamda_i, FUN = "-")
Y_nph = sweep(Y_n, 2, k, FUN = "/")
Y_nph[Y_nph <= 0] = 0.1

And then

     Y_nph <- log(Y_nph)

will give you data that you can plot.

Thank you!

I just gave the code a try and I got stuck on this step with a warning message:

Y_n = sweep(Y, 2, lamda_i, FUN = "-")

Warning message:
In max(cumDim[cumDim <= lstats]) :
no non-missing arguments to max; returning -Inf

Anything I might be doing wrong? The code runs through but there are just NA in the final log(Y_nph)

That error comes from some checking in sweep to make sure that the length of lambda_i is reasonable for the dimensions of the matrix you are sweeping on. So there appears to be a problem with either your Y matrix or whatever you are getting for lambda_i. You need to take a look at those data and see what's up.

I was trying to run it before calling the estNormalizationFactors. Fixed it now and have the output. Thank you bunches!

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