Hello, I am running my GeoMx Data with Standr, and it includes the "limma" package.

I am incorporating the codes from these two websites,

https://davislaboratory.github.io/GeoMXAnalysisWorkflow/articles/GeoMXAnalysisWorkflow.html#differential-expression-analysis-with-limma-voom-pipeline

https://ucdavis-bioinformatics-training.github.io/2018-June-RNA-Seq-Workshop/thursday/DE.html

and some parts are showing errors or unexpected results.

Despite the error below, I was able to run the next part of the limma DE gene analysis, but the result was 0 downreg and 0 upreg genes.

I suppose it may be due to the error below. It would be very much appreciated if someone could help.

The data structure may be a little different to scRNAseq data, since it is an spe object (SpatialExperiment class).

#Differential expression analysis with limma-voom pipeline

>library(edgeR)
>library(limma)

>HNdge <- SE2DGEList(HNspe_ruv)
>HNdesign <- model.matrix(~0 + biology + ruv_W1 + ruv_W2, data = colData(HNspe_ruv))

>mm <- model.matrix(~0 + Disease_status, data = colData(HNspe_ruv))

>y <- voom(mm, plot = F)

Error in approxfun(l, rule = 2, ties = list("ordered", mean)) : need at least two non-NA values to interpolate

fit <- lmFit(y, mm)
contr <- makeContrasts(groupI5.6 - groupC.6, levels = colnames(coef(fit)))
tmp <- contrasts.fit(fit, contr)
tmp <- eBayes(tmp)
top.table <- topTable(tmp, sort.by = "P", n = Inf)

HNcontr.matrix <- makeContrasts(
   BvT = Healthy - Disease,
   levels = colnames(HNdesign))


HNv <- voom(HNdge_all, HNdesign, plot = TRUE)

include your problematic code here with any corresponding output

y <- voom(mm, plot = F)

please also include the results of running the following in an R session

Error in approxfun(l, rule = 2, ties = list("ordered", mean)) : need at least two non-NA values to interpolate

sessionInfo( )

R version 4.4.1

package.version("limma") "3.60.3"

```

You are running voom on a design matrix rather than using your count data. Please re-read the help page for `voom', or more closely follow the vignette you point to (which uses the filtered count data).