20-kidney_differential_expression.Rmd

---
title: "Kidney differential expression analysis"
output:   
  html_notebook: 
    toc: true
    toc_float: true
---

**J. Taroni 2018**

In this notebook, we work with microdissected glomeruli data from patients with 
nephrotic syndrome, patients with ANCA-associated vasculitis, and living donors.

First, we'll apply the recount2 PLIER model and then we will test those LVs for
differential expression between the three groups.

## Functions and directory set up

```{r}
`%>%` <- dplyr::`%>%` 
source(file.path("util", "test_LV_differences.R"))
source(file.path("util", "plier_util.R"))
```

```{r}
# plot and result directory setup for this notebook
plot.dir <- file.path("plots", "20")
dir.create(plot.dir, recursive = TRUE, showWarnings = FALSE)
results.dir <- file.path("results", "20")
dir.create(results.dir, recursive = TRUE, showWarnings = FALSE)
```

## Read in data

### Expression data

```{r}
ercb.file <- file.path("data", "expression_data", 
                       "ERCB_Glom_CustCDF19_forVCRC.txt")
exprs.df <- readr::read_tsv(ercb.file)
exprs.df <- dplyr::select(exprs.df, -EntrezGeneID)
colnames(exprs.df)[1] <- "Gene"
```

```{r}
agg.exprs.df <- PrepExpressionDF(exprs.df)
# any genes that don't have a gene symbol need to be dropped
agg.exprs.df <- dplyr::filter(agg.exprs.df, !(is.na(Gene)))
readr::write_tsv(agg.exprs.df, path = file.path("data", "expression_data", 
                                                "ERCB_Glom_mean_agg.pcl"))
# as a matrix for use with PLIER
exprs.mat <- as.matrix(dplyr::select(agg.exprs.df, -Gene))
rownames(exprs.mat) <- agg.exprs.df$Gene
```

### Clinical data

```{r}
clinical.file <- file.path("data", "sample_info", "ERCB_glom_diagnosis.tsv")
diagnosis.df <- readr::read_tsv(clinical.file)
```

## Apply recount2 model

```{r}
# load model itself
recount.plier <- readRDS(file.path("data", "recount2_PLIER_data", 
                                   "recount_PLIER_model.RDS"))
# project
recount.b <- GetNewDataB(exprs.mat = as.matrix(exprs.mat),
                         plier.model = recount.plier)
```

```{r}
# save B matrix to file
b.file <- file.path(results.dir, "ERCB_glom_recount2_B.RDS")
saveRDS(recount.b, file = b.file)
```

## Differential expression

```{r}
LVTestWrapper(b.matrix = recount.b,
              sample.info.df = diagnosis.df,
              phenotype.col = "Diagnosis",
              file.lead = "ERCB_glom_recount2_model",
              plot.dir = plot.dir,
              results.dir = results.dir)
```