40-SLE_MCPcounter.Rmd

---
title: "SLE whole blood MCPcounter"
output: html_notebook
---

**J. Taroni 2018**

Are the expression values of the neutrophil-associated latent variables 
correlated with MCPCounter 
([Becht, et al.](https://doi.org/10.1186/s13059-016-1070-5)) neutrophil 
estimates?

The correlations between the neutrophil counts and the LV expression
levels are modest.
(This question has come up more than once!)
We think this is likely because neutrophils are terminally differentiated cells,
so it is a limitation of using gene expression as a measure of neutrophil count
rather than a limitation intrinsic to PLIER models or the MultiPLIER approach.

So, we'll check to see if the two estimates from expression are highly
correlated, which would lend support to this notion.

## Set up

```{r}
# magrittr pipe
`%>%` <- dplyr::`%>%`
```

#### Directory setup

```{r}
# plot and result directory setup for this notebook
plot.dir <- file.path("plots", "40")
dir.create(plot.dir, recursive = TRUE, showWarnings = FALSE)
results.dir <- file.path("results", "40")
dir.create(results.dir, recursive = TRUE, showWarnings = FALSE)
```

## Read in data

The SLE whole blood expression data

```{r}
sle.wb.file <- 
  file.path("data", "expression_data", 
            "SLE_WB_all_microarray_QN_zto_before_with_GeneSymbol.pcl")

exprs.mat <- readr::read_tsv(sle.wb.file) %>%
  dplyr::select(-EntrezID) %>%
  tibble::column_to_rownames("GeneSymbol") %>%
  as.matrix()
```

We'd like to compare this to results from `07-sle_cell_type_recount2_model`.

```{r}
plier.neutrophil.file <- file.path("results", "07", 
                                   "neutrophil_count_LV_both_models.tsv")
plier.neutrophil.df <- readr::read_tsv(plier.neutrophil.file)
```

## MCPCounter

```{r}
# get cell type estimates with MCPcounter
mcp.results <- 
  MCPcounter::MCPcounter.estimate(expression = exprs.mat,
                                  featuresType = "HUGO_symbols")

# we're only interested in the neutrophil counts
neutrophil.df <- reshape2::melt(mcp.results) %>%
  dplyr::filter(Var1 == "Neutrophils") %>% 
  dplyr::select(-Var1)
colnames(neutrophil.df) <- c("Sample", "Neutrophil_estimate")
```

## Compare

```{r}
joined.neutrophil.df <- dplyr::inner_join(neutrophil.df, plier.neutrophil.df,
                                          by = "Sample")
```

```{r}
cor(joined.neutrophil.df$recount2_LV603,
    joined.neutrophil.df$Neutrophil_estimate, 
    method = "pearson") ^ 2
```

### Save results

```{r}
readr::write_tsv(joined.neutrophil.df,
                 path = file.path(results.dir, 
                                  "Banchereau_MCPcounter_neutrophil_LV.tsv"))
```