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Unico

We present Unico, a unified cross-omics method designed to deconvolve standard 2-dimensional bulk matrices of samples by features into a 3-dimensional tensors representing samples by features by cell types. Unico stands out as the first principled model-based deconvolution method that is theoretically justified for any heterogeneous genomic data.

All necessary scripts used for the analyses reported in the manuscript can be found under folder Rscripts

Unico will be available soon on CRAN as an R package

Install from GitHub

if (!require("devtools", quietly = TRUE))
    install.packages("devtools")
devtools::install_github("https://github.com/cozygene/Unico")

Version info

Our package is tested on both R 3.6.1 and R 4.1.0, on Windows, Linux and MacOS based machines.

Tutorial

Please head to this vignette for a step by step tutorial on (1) deconvolving a simulated PBMC pseudo-bulk expression dataset and (2) association testing on subsets of publicly available methylation datasets.

Author

This software is developed by Zeyuan Johnson Chen (johnsonchen@cs.ucla.edu) and Elior Rahmani (EliorRahmani@mednet.ucla.edu).

License

Unico is available under the GPL-3 license.

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Version

Install

install.packages('Unico')

Monthly Downloads

214

Version

0.1.0

License

GPL-3

Maintainer

Zeyuan Chen

Last Published

February 26th, 2024

Functions in Unico (0.1.0)

association_parametric

Performs parametric statistical testing
tensor

Inferring the underlying source-specific 3D tensor
simulate_data

Simulate data under Unico model assumption
Unico

Fitting the Unico model
association_asymptotic

Performs asymptotic statistical testing under no distribution assumption