I am trying to analyse my transcript data to generate heat maps, PCAs and see the differential expression between samples. I don't necessarily need the coldata, as I already know the conditions for each sample name but if so, it would be location, West, Mid and East.

sample  location
X1473   Mid
X1475   Mid
X1528   Mid
X1584   East
X1585   East
X1586   East
X1678   West
X1679   West
X1680   West
BLANK   None

I have a matrix with read counts prepared from another source "df" such as:

# A tibble: 1,864 x 11
   func                            X1473 X1475 X1528 X1584 X1585 X1586 X1678 X1679 X1680 blank
   <chr>                           <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
 1 1-5-phosphoribosyl-5-5-phosphor…   93    81    36    58    45    26    32    57    65   0
 2 1-5-phosphoribosyl-5-amino-4-im…    11    20     6     7    14     5     4     7    13    0
 3 1-acyl-sn-glycerol-3-phosphate …   96    76    43    50    88    39    42    61    62   1
 4 1-deoxy-D-xylulose-5-phosphate …   192   169    79    95   134    77    71   148   133  1
 5 1-deoxy-D-xylulose-5-phosphate …   557   722   303   700   935   507   275   594   694  2

Following the DESEq2 tutorial https://www.bioconductor.org/packages/devel/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#indfilt I have tried to use

library("pasilla")
pasCts <- system.file("extdata",
                      "pasilla_gene_counts.tsv",
                      package="pasilla", mustWork=TRUE)
pasAnno <- system.file("extdata",
                       "pasilla_sample_annotation.csv",
                       package="pasilla", mustWork=TRUE)
cts <- as.matrix(read.csv(pasCts,sep="\t",row.names="gene_id"))
coldata <- read.csv(pasAnno, row.names=1)
coldata <- coldata[,c("condition","type")]

I am unsure how each file has to look like, as maybe "extdata" is meant to contain the gene ID but not the annotation already? What if I already have the count matrix with the count reads and annotations as shown above? What is the best way to start with the differential expression analysis with my count matrix with annotated genes? Cheers,

Try this tutorial instead:

https://bioconductor.org/packages/release/workflows/vignettes/rnaseqGene/inst/doc/rnaseqGene.html#starting-from-count-matrices