Running tutorial error at vizAllTopics

[LJ-dotcom]

Hello,
I am running the combining datasets tutorial with the MOB dataset.
Everything works fine until the first call of vizAllTopics:

library(STdeconvolve)
## load built in data
data(mOB)
pos <- mOB$pos
cd <- mOB$counts
annot <- mOB$annot

mobCorpus <- preprocess(t(mOB$counts),
                       extractPos = FALSE,
                       selected.genes = NA,
                       nTopGenes = NA,
                       genes.to.remove = NA,
                       removeAbove = NA,
                       removeBelow = NA,
                       min.reads = 100,
                       min.lib.size = 100,
                       min.detected = 1,
                       ODgenes = TRUE,
                       nTopOD = NA,
                       od.genes.alpha = 0.05,
                       gam.k = 5,
                       verbose = TRUE)

## choose optimal number of cell-types
ldas <- fitLDA(t(as.matrix(mobCorpus$corpus)), Ks = seq(2, 15, by = 1), ncores = 7)
## get best model results
optLDA <- optimalModel(models = ldas, opt = 12)
## extract deconvolved cell-type proportions (theta) and transcriptional profiles (beta)
results <- getBetaTheta(optLDA, perc.filt = 0.05, betaScale = 1000)
deconProp <- results$theta
deconGexp <- results$beta
## visualize deconvolved cell-type proportions
vizAllTopics(deconProp,
             pos, 
             groups = annot,
             group_cols = rainbow(length(levels(annot))),
             r=0.4)

The error I get is:

Error in `$<-.data.frame`(`*tmp*`, "Pixel.Groups", value = c("3: Outer Plexiform Layer",  : 
  replacement has 260 rows, data has 0

The only part of the code that I changed was in the fitLDA function, which I changed the input from corpus to mobCorpus$corpus since it was throwing an error.

Thanks for your help/time!

[LJ-dotcom]

I removed
mobCorpus <- preprocess(t(mOB$counts), extractPos = FALSE, selected.genes = NA, nTopGenes = NA, genes.to.remove = NA, removeAbove = NA, removeBelow = NA, min.reads = 100, min.lib.size = 100, min.detected = 1, ODgenes = TRUE, nTopOD = NA, od.genes.alpha = 0.05, gam.k = 5, verbose = TRUE)

And put in
counts <- cleanCounts(cd, min.lib.size = 100, min.reads = 10)
corpus <- restrictCorpus(counts, removeAbove=1.0, removeBelow = 0.05, nTopOD = 1000)

And it solved the issue!
Maybe the object corpus in ldas <- fitLDA(t(as.matrix(corpus)), Ks = seq(2, 15, by = 1), ncores = 7) was stored previously in an R studio session and was being called accidentally?

The full code that worked is here:

library(STdeconvolve)
## load built in data
data(mOB)
pos <- mOB$pos
cd <- mOB$counts
annot <- mOB$annot
counts <- cleanCounts(cd, min.lib.size = 100, min.reads = 10)
corpus <- restrictCorpus(counts, removeAbove=1.0, removeBelow = 0.05, nTopOD = 1000)

## choose optimal number of cell-types
ldas <- fitLDA(t(as.matrix(corpus)), Ks = seq(2, 15, by = 1), ncores = 7)
## get best model results
optLDA <- optimalModel(models = ldas, opt = 12)
## extract deconvolved cell-type proportions (theta) and transcriptional profiles (beta)
results <- getBetaTheta(optLDA, perc.filt = 0.05, betaScale = 1000)
deconProp <- results$theta # x cell type proportion matrix
deconGexp <- results$beta
## visualize deconvolved cell-type proportions
vizAllTopics(theta = deconProp, 
             pos = pos,
             groups = annot,
             group_cols = rainbow(length(levels(annot))),
             r=0.4)