compare two sets of biopsies.

1 Mosser and TMRC biopsies, together at last.

annot <- load_biomart_annotations()

## The biomart annotations file already exists, loading from it.

biopsies <- create_expt(metadata="sample_sheets/all_samples.xlsx",
                        gene_info=annot[["annotations"]])

## Reading the sample metadata.

## The sample definitions comprises: 11 rows(samples) and 5 columns(metadata fields).

## Matched 21481 annotations and counts.

## Bringing together the count matrix and gene information.

## Saving the expressionset to 'expt.rda'.

## The final expressionset has 21481 rows and 11 columns.

nb <- normalize_expt(biopsies, transform="log2", convert="cpm", norm="quant", filter=TRUE)

## Removing 7927 low-count genes (13554 remaining).

## transform_counts: Found 76 values equal to 0, adding 1 to the matrix.

plot_pca(nb)$plot

only_b1 <- subset_expt(biopsies, subset="batch=='b1'")

## subset_expt(): There were 11, now there are 8 samples.

b1 <- normalize_expt(only_b1, transform="log2", convert="cpm", norm="quant", filter=TRUE)

## Removing 8167 low-count genes (13314 remaining).

## transform_counts: Found 54 values equal to 0, adding 1 to the matrix.

plotted <- plot_pca(b1)$plot
pp(file="images/wellcome_only_b1_pca.png", image=plotted)

pander::pander(sessionInfo())
message(paste0("This is hpgltools commit: ", get_git_commit()))
this_save <- paste0(gsub(pattern="\\.Rmd", replace="", x=rmd_file), "-v", ver, ".rda.xz")
message(paste0("Saving to ", this_save))
tmp <- sm(saveme(filename=this_save))