03_differential_expression.Rmd

---
title: "Differential Expression for TNSeq of Spyogenes. (2017)"
author: "atb"
date: "`r Sys.Date()`"
output:
 html_document:
  code_download: true
  code_folding: show
  fig_caption: true
  fig_height: 7
  fig_width: 7
  highlight: default
  keep_md: false
  mode: selfcontained
  number_sections: true
  self_contained: true
  theme: readable
  toc: true
  toc_float:
    collapsed: false
    smooth_scroll: false
---

<style>
  body .main-container {
    max-width: 1600px;
}
</style>

```{r options, include=FALSE}
## These are the options I tend to favor
library("hpgltools")
tt <- devtools::load_all("~/hpgltools")
knitr::opts_knit$set(progress=TRUE,
                     verbose=TRUE,
                     width=90,
                     echo=TRUE)
knitr::opts_chunk$set(error=TRUE,
                      fig.width=8,
                      fig.height=8,
                      dpi=96)
options(digits=4,
        stringsAsFactors=FALSE,
        knitr.duplicate.label="allow")
ggplot2::theme_set(ggplot2::theme_bw(base_size=10))
set.seed(1)
previous_file <- "02_sample_estimation.Rmd"
ver <- "20180717"

tmp <- sm(loadme(filename=paste0(gsub(pattern="\\.Rmd", replace="", x=previous_file), "-v", ver, ".rda.xz")))

rmd_file <- "03_differential_expression.Rmd"
```

# Differential Expression, Spyogenes: `r ver`

This worksheet performs a set of pairwise comparisons of the counts for this tnseq experiment
given the sva surrogate adjustments.

This is being performed via limma/edger/deseq2, which one may rightly argue is not
entirely appropriate for TNSeq data.  On the other hand, as a general metric of
changing fitness, it provides some interesting information.

```{r initial_estimation, fig.show="hide"}
initial_diff <- all_pairwise(input=rpmi_filt, model_batch="fsva")

keepers <- list("t2t1" = c("rpmi_t2", "thy_t1"),
                "t3t1" = c("rpmi_t3", "thy_t1"),
                "t2zn" = c("rpmi_t2_highzn", "rpmi_t2_lowzn"),
                "t3zn" = c("rpmi_t3_highzn", "rpmi_t3_lowzn"),
##                "t2cu" = c("rpmi_t2_highcu", "rpmi_t2_lowcu"),
##                "t3cu" = c("rpmi_t3_highcu", "rpmi_t3_lowcu"),
                "time_highzn" = c("rpmi_t3_highzn", "rpmi_t2_highzn"),
                "time_lowzn" = c("rpmi_t3_lowzn", "rpmi_t2_lowzn"),
##                "time_highcu" = c("rpmi_t3_highcu", "rpmi_t2_highcu"),
##                "time_lowcu" = c("rpmi_t3_lowcu", "rpmi_t2_lowcu"),
                "t2_rpmi_highzn" = c("rpmi_t2_highzn", "rpmi_t2"),
                "t3_rpmi_highzn" = c("rpmi_t3_highzn", "rpmi_t3"),
                "t2_rpmi_lowzn" = c("rpmi_t2_lowzn", "rpmi_t2"),
                "t3_rpmi_lowzn" = c("rpmi_t3_lowzn", "rpmi_t3")
##                "t2_rpmi_highcu" = c("rpmi_t2_highcu", "rpmi_t2"),
##                "t3_rpmi_highcu" = c("rpmi_t3_highcu", "rpmi_t3"),
##                "t2_rpmi_lowcu" = c("rpmi_t2_lowcu", "rpmi_t2"),
##                "t3_rpmi_lowcu" = c("rpmi_t3_lowcu", "rpmi_t3"))
                )
initial_write <- combine_de_tables(all_pairwise_result=initial_diff,
                                   excel=paste0("excel/initial_diff-v", ver, ".xlsx"),
                                   keepers=keepers)
sig_write <- sm(extract_significant_genes(initial_write,
                                          excel=paste0("excel/significant-v", ver, ".xlsx")))
```

```{r saveme}
message(paste0("This is hpgltools commit: ", get_git_commit()))
pander::pander(sessionInfo())
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))
```