UNITE software

This repository contains the code and resources used in the UNITE paper by the Rosenfeld Group. It includes instructions for setting up the analysis environment, accessing raw data and extracted features, using trained models, and running UNITE on new shallow whole-genome sequencing data. The codes are uploaded to this Zenodo record as a 3.9GB zip file (Please scroll to the bottom of the page to see the files session, access is restricted). Please contact bci-nrlab-admin@qmul.ac.uk for access. UNITE-paper Contents Using the pre-built Conda environment Raw data Features extracted from raw data Docker image Trained models Running UNITE on new data Key resources License 1. Using the pre-built Conda environment This repository provides a pre-built Conda environment, R4_1.tar.gz, for fully reproducible analysis on Linux systems, including HPC or local Linux machines. This file was generated using conda-pack. The environment can be used with micromamba, which is recommended, or Miniconda. If conda or mamba is already installed, no additional installation is required. Install micromamba curl -Ls https://micro.mamba.pm/api/micromamba/linux-64/latest | tar -xvj bin/micromamba chmod +x bin/micromamba export PATH="$PWD/bin:$PATH" micromamba shell init -s bash -p ~/micromamba source ~/.bashrc Download and unpack the environment Download R4_1.tar.gz, approximately 3.4 GB, from Zenodo: https://doi.org/10.5281/zenodo.18187489 Choose where to install the environment, for example: mkdir -p ~/conda_envs/R4_1 Unpack the environment: tar -xzf R4_1.tar.gz -C ~/conda_envs/R4_1 Fix paths This step is required. conda activate ~/conda_envs/R4_1 Alternatively, if using micromamba: micromamba activate ~/conda_envs/R4_1 Then run: conda-unpack Activate the environment conda activate ~/conda_envs/R4_1 Alternatively, if using micromamba: micromamba activate ~/conda_envs/R4_1 Verify the environment This step verifies that the environment works as expected. Open the R console and run: library(pacman) packages