ROSMAP-variables.Rmd

---
title: "Define ROSMAP Variables"
description: |
 This script first performs preprocessing of ROSMAP FPKM and covariate data so that they have same order, then defines variables in the covariate data.
output:
  distill::distill_article:
    toc: true
---

```{r setup, include = FALSE}
knitr::opts_chunk$set(eval = FALSE)
```


# Dependencies

Load requisite packages.

```{r load-packages}

library(data.table)

```


# Read FPKM Data

Read FPKM data, remove the version from Ensembl ID, and remove duplicated samples.

```{r fpkm-data}

# read FPKM data
fpkm_file = "../Data/ROSMAP_RNAseq_FPKM_gene.tsv"
rosmap_fpkm = fread(fpkm_file, stringsAsFactors = FALSE, header = T, sep = "\t")
all(rosmap_fpkm$tracking_id == rosmap_fpkm$gene_id)
gene_id = rosmap_fpkm$gene_id
rosmap_fpkm = rosmap_fpkm[, c(-1,-2), with = F]
rosmap_fpkm = as.data.frame(rosmap_fpkm)

# remove version from Ensembl ID
rownames(rosmap_fpkm) = gsub("\\.\\d*$", "", gene_id)

# remove duplicated samples
duplicate_sample_ids = c("492_120515_0","492_120515_6")
rosmap_fpkm = rosmap_fpkm[, -which(colnames(rosmap_fpkm) %in% duplicate_sample_ids)]

```


# Read Covariate Data

Read ROSMAP ID mapping file.

```{r rosmap-map}

# read ROSMAP ID map
key_map_file = "../Data/ROSMAP_IDkey.csv"
key_map = fread(key_map_file)
key_map = unique(key_map[, .(projid, mrna_id)])

```

Read and pre-process covariate data.

```{r covariate-data}

# read and process covariate data
cov_file = "../Data/ROSMAP_clinical.csv"
cov = fread(cov_file)

# rename covariate data and merge with ROSMAP IDs
setnames(cov, c("projid", "cts_mmse30_lv", "braaksc", "ceradsc", "cogdx", "apoe_genotype"), 
         c("projid", "MMSE", "Braak", "CERAD", "ClinicalDiagnosis", "RawAPOE"))
cov[key_map, on = .(projid), mrna_id := mrna_id]

# no version number
cov[, mrna_id_nov := gsub("_\\d$", "", mrna_id)]

```


# Reorder Data

```{r reorder-data}

# extract clinical data in the same order as in the data
colnames(rosmap_fpkm) = gsub("_\\d$", "", colnames(rosmap_fpkm)) 

# remove samples without clinical data
colnames(rosmap_fpkm)[!colnames(rosmap_fpkm) %in% c(cov$mrna_id_nov)]
rosmap_fpkm = rosmap_fpkm[, colnames(rosmap_fpkm) %in% cov$mrna_id_nov]
all(colnames(rosmap_fpkm) %in% cov$mrna_id_nov)
cov = cov[data.table(mrna_id_nov = colnames(rosmap_fpkm)), on = .(mrna_id_nov)]

# check that cov and rosmap_fpkm have same order
all(cov$mrna_id_nov == colnames(rosmap_fpkm))
colnames(rosmap_fpkm) = cov$projid

```


# Define Clinical Variables

## Braak

<p>Group levels into three categories:</p>
<ul>
  <li>`1` = `Normal/I/II`</li>
  <li>`2` = `III/IV`</li>
  <li>`3` = `V/VI`</li>
</ul>

```{r braak}

# refactor
cov[, B := as.factor(cov$Braak)]
levels(cov$B) = c(1,1,1,2,2,3,3)
cov[, B := as.character(B)]
cov[, B := factor(B)]

# double-check
table(cov$B, cov$Braak)

```

## CERAD

<p>Old ROSMAP levels:</p>
<ul>
  <li>`1` = `Definite`</li>
  <li>`2` = `Probable`</li>
  <li>`3` = `Possible`</li>
  <li>`4` = `Normal`</li>
</ul>

<p>Define new levels:</p>
<ul>
  <li>`1` = `Normal`</li>
  <li>`2` = `Possible`</li>
  <li>`3` = `Probable`</li>
  <li>`4` = `Definite`</li>
</ul>

```{r cerad}

# refactor
cov[, C := as.factor(CERAD)]
levels(cov$C) = c(3,2,1,0)
cov[, C := as.character(C)]
cov[, C := factor(C)]

# double-check
table(cov$C, cov$CERAD)

```

## APOE

<p>Group levels into three categories:</p>
<ul>
  <li>`E2` = `E2/E2` and `E2/E3`</li>
  <li>`E3` = `E3/E3`</li>
  <li>`E4` = `E2/E4`, `E3/E4`, and `E4/E4`</li>
</ul>

```{r apoe}

# refactor
cov[, APOE := as.factor(RawAPOE)]
levels(cov$APOE) = c("E2", "E2", "E4", "E3", "E4", "E4")
cov[, E := as.character(APOE)]
cov[, E := factor(E, levels = c("E3", "E2", "E4"))]

# double-check
table(cov$E, cov$RawAPOE)

```

## E4 Count

<p>Group levels into three categories:</p>
<ul>
  <li>`0` = `E2/E2`, `E3/E3`, and `E2/E3`</li>
  <li>`1` = `E2/E4` and `E3/E4`</li>
  <li>`2` = `E4/E4`</li>
</ul>

```{r e4-count}

# refactor
cov[, E4num := as.factor(RawAPOE)]
levels(cov$E4num) = c(0, 0, 1, 0, 1, 2)
cov[, E4num := as.numeric(as.character(E4num))]

# double-check
table(cov$E4num, cov$RawAPOE)

```

## E2 Count

<p>Group levels into three categories:</p>
<ul>
  <li>`0` = `E4/E4`, `E3/E3`, and `E3/E4`</li>
  <li>`1` = `E2/E4` and `E2/E3`</li>
  <li>`2` = `E2/E2`</li>
</ul>

```{r e2-count}

# refactor
cov[, E2num := as.factor(RawAPOE)]
levels(cov$E2num) = c(2, 1, 1, 0, 0, 0)
cov[, E2num := as.numeric(as.character(E2num))]

# double-check
table(cov$E2num, cov$RawAPOE)

```

## Age at Death

Clean age at death variable.

```{r age-death}

# clean age at death
cov[, age_at_death := gsub("90\\+", "91", age_death)]
cov[, age_at_death := as.numeric(age_at_death)]

```


# Save Results

```{r save-results}

# save results
rosmap = list(fpkm = rosmap_fpkm,
              cov = cov)
save(rosmap, file = "../Data/ROSMAP-24.Rdata")

```