RNAseq of L.panamensis: Biopsy Differential Expression.

1 Differential Expression, Biopsy: 20171110

hs_biopsy_filt <- sm(normalize_expt(hs_biopsy, filter=TRUE))
keepers <- list("sh_nil" = c("pbmc_sh", "pbmc_nil"),
                "ch_nil" = c("pbmc_ch", "pbmc_nil"),
                "ch_sh" = c("pbmc_ch", "pbmc_sh"))

1.1 Perform a quick and dirty differential expression

I think it is not likely that we will be able to use these analyses given the lack of complete experimental design. So I will just run a quick and dirty try and see if anything comes out of it.

hs_biopsy_diff <- all_pairwise(hs_biopsy_filt, model_batch="sva")

## The be method chose 1 surrogate variable(s).

## Estimate type 'sva' is shorthand for 'sva_unsupervised'.

## Other sva options include: sva_supervised and svaseq.

## Attempting sva unsupervised surrogate estimation with 1 surrogates.

## Using sva to visualize before/after batch inclusion.

## Performing a test normalization with: raw

## Finished running DE analyses, collecting outputs.

## Comparing analyses 1/6: post_fail_vs_post_cure

## Comparing analyses 2/6: pre_cure_vs_post_cure

## Comparing analyses 3/6: pre_fail_vs_post_cure

## Comparing analyses 4/6: pre_cure_vs_post_fail

## Comparing analyses 5/6: pre_fail_vs_post_fail

## Comparing analyses 6/6: pre_fail_vs_pre_cure

hs_biopsy_combined <- combine_de_tables(hs_biopsy_diff)

## Writing a legend of columns.

## Working on table 1/6: post_fail_vs_post_cure

## Working on table 2/6: pre_cure_vs_post_cure

## Working on table 3/6: pre_fail_vs_post_cure

## Working on table 4/6: pre_cure_vs_post_fail

## Working on table 5/6: pre_fail_vs_post_fail

## Working on table 6/6: pre_fail_vs_pre_cure

some_plots <- extract_de_plots(hs_biopsy_diff, type="deseq", table="post_fail_vs_post_cure")
some_plots$ma$plot

if (!isTRUE(get0("skip_load"))) {
  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))
}

## If you wish to reproduce this exact build of hpgltools, invoke the following:

## > git clone http://github.com/abelew/hpgltools.git

## > git reset 8ab5e84e45dc827333f9c2905f96a7c3223ff92f

## R> packrat::restore()

## This is hpgltools commit: Tue Apr 3 11:33:10 2018 -0400: 8ab5e84e45dc827333f9c2905f96a7c3223ff92f

## Saving to 02_expression_biopsy-v20171110.rda.xz