Rectangle

Rectangle is an open-source Python package for single-cell-informed cell-type deconvolution of bulk and spatial transcriptomic data, which is part of the scverse ecosystem.

Rectangle presents a novel approach to second-generation deconvolution, characterized by hierarchical signature building for fine-grained cell-type deconvolution, estimation and correction of unknown cellular content, and efficient handling of large-scale single-cell data during signature matrix computation.

Rectangle was developed to overcome the current challenges in cell-type deconvolution, providing a robust and accurate methodology while ensuring a low computational profile.

Getting started

Please refer to the documentation. In particular, the

• Tutorials for a step-by-step guide on how to use Rectangle, and the

• API documentation.

Installation

You need Python 3.10–3.12 installed on your system.

How to install Rectangle:

Install the latest release of Rectangle from PyPI https://pypi.org/project/rectanglepy/:

pip install rectanglepy

How Rectangle works

Rectangle performs robust multiscale deconvolution informed by single-cell transcriptomics. Rectangle takes annotated scRNA-seq data and a bulk RNA-seq mixture as input. In the signature-building phase, it performs bootstrapped pseudobulking of the scRNA-seq data, followed by signature-gene selection based on log-fold-change (logFC) and p-value, and signature-matrix optimization (minimizing the condition number and correcting for cell-type-specific mRNA content bias). Based on this, it constructs two signature matrices: a “direct signature”, resolving individual cell types, and a “clustered signature” grouping transcriptionally similar cell types. In the deconvolution phase, Rectangle first uses the clustered signature to deconvolve the bulk data into coarse cell-type estimates. These are then used to constrain a second deconvolution step that leverages the direct signature to resolve individual cell-type fractions. Finally, the resulting estimates are scaled to account for unknown cellular content not represented in the reference.

License

Rectangle is dual-licensed: BSD-3-Clause OR Commercial.

Open-source option: BSD-3-Clause

You may use, modify, and redistribute Rectangle, including in proprietary products, if you keep the copyright and license notices and do not use the authors’ names for endorsement.

See LICENSE.

Commercial option

For alternative terms, such as warranties, indemnities, dedicated support, SLAs, or redistribution without BSD notice requirements, contact innovation-psb@uibk.ac.at.

See LICENSE-Commercial.md.

Release notes

See the changelog.

Contact

If you found a bug, please use the issue tracker.

For commercial licensing: innovation-psb@uibk.ac.at

Citation

If you use Rectangle in your project, please cite:

Eder B, Rigato I, Dietrich A, Merotto L, Sturm G, Treis T, List M, Theis FJ, Finotello F. Rectangle: robust and scalable multiscale deconvolution informed by single-cell RNA sequencing data. bioRxiv. 2026. doi:10.64898/2026.07.07.736950