---
title: "Reproducibility with seeker"
author: "Jake Hughey"
date: "`r Sys.Date()`"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Reproducibility with seeker}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r setup, include = FALSE}
knitr::opts_chunk$set(collapse = TRUE, comment = '#>')
```

Using the `seeker` package together with docker, it's easy to make fetching and processing of sequencing and microarray data completely reproducible. First pull the latest version of the [socker](https://github.com/hugheylab/socker) image, which has `seeker` and its dependencies already installed.

```{sh, eval = FALSE}
docker pull ghcr.io/hugheylab/socker
```

## RNA-seq data

The `seeker` package includes an example yaml file, R script, and shell script for fetching and processing a subset of an RNA-seq dataset. Here we'll download the files from GitHub to avoid having to install the package locally:

```{r, eval = FALSE}
urlBase = 'https://raw.githubusercontent.com/hugheylab/seeker/master/inst/extdata/'
for (filename in c('PRJNA600892.yml', 'run_seeker.R', 'run_seeker.sh')) {
  download.file(paste0(urlBase, filename), filename)}
```

PRJNA600892.yml:

```{r, code = readLines(system.file('extdata', 'PRJNA600892.yml', package = 'seeker')), eval = FALSE}
```

run_seeker.R:

```{r, code = readLines(system.file('extdata', 'run_seeker.R', package = 'seeker')), eval = FALSE}
```

run_seeker.sh:

```{r, code = readLines(system.file('extdata', 'run_seeker.sh', package = 'seeker')), eval = FALSE}
```

Now simply run the shell script:

```{sh, eval = FALSE}
sh run_seeker.sh
```

The output will appear in your working directory. You can follow `seeker()`'s progress using the log file. To process a different dataset, modify the yaml file and shell script accordingly. Beware this example uses "salmon_partial_sa_index" from refgenie to minimize computational requirements; for actual use we recommend "salmon_sa_index".

## Microarray data

The `seeker` package also includes an example yaml file, R script, and shell script for fetching and processing a microarray dataset. Download the files to your working directory:

```{r, eval = FALSE}
urlBase = 'https://raw.githubusercontent.com/hugheylab/seeker/master/inst/extdata/'
for (filename in c('GSE25585.yml', 'run_seeker_array.R', 'run_seeker_array.sh')) {
  download.file(paste0(urlBase, filename), filename)}
```

GSE25585.yml:

```{r, code = readLines(system.file('extdata', 'GSE25585.yml', package = 'seeker')), eval = FALSE}
```

run_seeker_array.R:

```{r, code = readLines(system.file('extdata', 'run_seeker_array.R', package = 'seeker')), eval = FALSE}
```

run_seeker_array.sh:

```{r, code = readLines(system.file('extdata', 'run_seeker_array.sh', package = 'seeker')), eval = FALSE}
```

Now simply run the shell script:
```{sh, eval = FALSE}
sh run_seeker_array.sh
```

The output will appear in your working directory. You can follow `seekerArray()`'s progress using the log file. To process a different dataset, modify the yaml file and shell script accordingly.