... It's in the database that way:
> con <- dbConnect(SQLite(), paste0(path.package("EnsDb.Mmusculus.v79"), "/extdata/EnsDb.Mmusculus.v79.sqlite"))
> dbGetQuery(con, "select * from gene where gene_id='ENSMUSG00000079658';")
gene_id gene_name entrezid gene_biotype gene_se ...
... Most of your questions could be characterized as asking how you should analyze your data. However, this support site is intended to help people with technical problems using Bioconductor software.
Analyzing data is a non-trivial task, in many ways much more difficult than simply figuring out how to ...
... The arrays used for that experiment were custom one-color arrays, so you have to specify the columns by hand:
> z <- read.maimages(dir(".", "^GSM"), columns = list(R = "F635 Median", Rb = "B635 Median"))
Read GSM249529.gpr.gz ...
... Do note that R is case sensitive, so you cannot pass 'ensgene' as an argument when the function expects 'ensGene':
tablename track subtrack GeneID
1 knownGene UCSC Genes <NA> Entrez Gene ID
10 vegaGene ...
... The phenoData slot contains information about the columns of your ExpressionSet, not the rows.
... Usually I do something like
bams <- dir("../", "bam$", full.names = TRUE)
bfl <- BamFileList(bams, asMates = TRUE)
ex <- exonsBy(TxDb.Drerio.UCSC.danRer10.refGene, "gene")
ex <- reduce(ex)
SE <- summarizeOverlaps(ex, bfl, singleEnd = FAL ...
... Rather than trying to hack things by calling ggplot2 functions directly, you might just read the help page for plotPCA, which says
size_by: character string defining the column of 'pData(object)' to be
used as a factor by which to define the size of points in the
plot. Alternat ...