That restricts your choice to packages that support mouse chromosomes, immediately excluding e.g. the GenomeGraphs and quantsmooth bioconductor packages because they support only human ideograms, but the Gviz Bioconductor package does support genomes in Ensembl and UCSC. From the examples, it looks like it is the most efficient way of making publication ready ideograms with your data right now. Step through the examples in the package vignettes and try them out.

Here is one example that makes such a plot, I display only two data tracks but you will manage, you need to install the Gviz package in R before:

library(IRanges)
library(Gviz)
gen <- "mm9" # mouse genome
chr <- "chr7" # chromosome 7

## make some markers
anot1 = IRanges(start=runif(100, min=1, max=152524553), width=1)
anot2 = IRanges(start=runif(100, min=1, max=152524553), width=1)
## ideogram:
itrack <- IdeogramTrack(genome = gen, chromosome = chr)
## axis:
gtrack <- GenomeAxisTrack()
## plot:
atrack1 <- AnnotationTrack(anot1, chromosome = chr,
genome = gen, name = "Sample1")
atrack2 <- AnnotationTrack(anot2, chromosome = chr,
genome = gen, name = "Sample2")
plotTracks(list(itrack, gtrack, atrack1, atrack2))