Installation Guide

System Requirements

Julia: 1.10 or higher
CPU: Multiple cores and threads recommended. Increasing the number of threads reduces computation time.
RAM: >=16GB recommended. RAM availability should exceed the spectral library size by at least 4GB. For searching against the yeast proteome, as little as 6-8 GB may suffice.
Storage: SSD recommended. Available disk space at least double the total size of the .arrow formmated raw files to search. The .arrow files are usually ~1/2 the size of the vendor files.
Operating System: Windows, Linux, or macOS

Installation

End-User Installation

Download the installer for your operating system from the releases page.
Run the installer. It places a pioneer executable on your PATH.
On first launch:
- Windows/Linux – pioneer downloads IntelOpenMP and MKL the first time it runs.
- macOS – Gatekeeper verifies the binary and the first run can take about a minute. Zipped binaries require manual Gatekeeper approval and are not recommended.
Verify the installation:
```
pioneer --help
```

Docker

Run Pioneer in a container without installing dependencies.

Pull the prebuilt image:

docker pull dennisgoldfarb/pioneer:latest

Execute Pioneer inside the container, mounting a host directory (e.g. the current directory) to access data:
```
docker run --rm -it -v $(pwd):/work dennisgoldfarb/pioneer:latest pioneer --help
```
Replace pioneer --help with any subcommand.
To build the image locally using the included Dockerfile:
```
docker build -t pioneer .
```

Development Setup

To work on Pioneer itself, set up a local development environment.

Install Julia 1.10 or higher from julia.org.

Clone the repository:

git clone https://github.com/nwamsley1/Pioneer.jl.git
cd Pioneer.jl

Start Julia in the development environment and activate the project:
```
julia --project=dev
pkg> develop ./
```
In the Julia REPL load Revise and Pioneer:
```
julia> using Revise, Pioneer
```
Install PioneerConverter to convert Thermo RAW files to Arrow format.

Call the main functions directly, e.g.

params = GetBuildLibParams(out_dir, lib_name, fasta_dir)
BuildSpecLib(params)
params = GetSearchParams("library.poin", "ms_data", "results")
SearchDIA(params)

Subcommand	Julia function
`params-predict`	`GetBuildLibParams`
`predict`	`BuildSpecLib`
`params-search`	`GetSearchParams`
`search`	`SearchDIA`
`convert-raw`	`PioneerConverter`
`convert-mzml`	`convertMzML`

'note'

Revise enables hot reloading of code during development.

PioneerConverter

Detailed installation and usage instructions for PioneerConverter are available in its documentation.

Next Steps

After installation:

Follow the Quick Start Tutorial.
Generate parameter files with pioneer params-predict or pioneer params-search, then edit them according to Parameter Configuration.