Count normalization with DESeq2 - Answer key

Exercise 1

Suppose we have sample names matching in the counts matrix and metadata file, but they are in different order. Write the line(s) of code to create a new matrix with columns re-ordered such that they are identical to the row names of the metadata.

There are multiple ways to do this. For example:

idx <- match(rownames(meta), colnames(data))
data_reordered <- data[, idx]

data_reordered <- data[, match(rownames(meta), colnames(data))]

txi$counts <- txi$counts[, match(rownames(meta), colnames(txi$counts))]

---
title: "Count normalization with DESeq2 - Answer key"
---

```{r data_setup}
#| echo: false

# load objects needed to render this lesson
txi  <- readRDS("./data/intermediate_txi.RDS")
meta <- readRDS("./data/metadata.RDS")
data <- readRDS("./data/intermediate_txi_counts.RDS")
```

# Exercise 1

**Suppose we have sample names matching in the counts matrix and metadata file, but they are in different order. Write the line(s) of code to create a new matrix with columns re-ordered such that they are identical to the row names of the metadata.**

There are multiple ways to do this. For example:

```{r}
idx <- match(rownames(meta), colnames(data))
data_reordered <- data[, idx]
```

OR

```{r}
data_reordered <- data[, match(rownames(meta), colnames(data))]
```

OR

```{r}
txi$counts <- txi$counts[, match(rownames(meta), colnames(txi$counts))]
```