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Deconvolution Project

This repository contains two distinct codebases associated with the study "Systematic Assessment of the Biological Impact of Cellular Deconvolution on Downstream Analyses of Disease Transcriptomes" by Sanga Mitra†, Maziya Ibrahim†, and Manikandan Narayanan, where † denotes equal contribution.

Deconvolution_Main_Code

This folder contains scripts for:

-Deconvolution of bulk RNA-seq data

-Differential gene expression analysis to generate cell type–corrected expression profile

-Pseudobulk analysis of single-nucleus RNA-seq (snRNA-seq) data

Developer: Maziya Ibrahim

Deconvolution_Downstream_Analyses

This folder contains scripts for all downstream analyses performed on the differentially expressed genes.

The code enables users to:

-Perform the downstream statistical and biological analyses described in the study

-Reproduce the figures and tables presented in the manuscript

A detailed description of the analysis workflow, required inputs, and methods is provided within this folder.

Developer: Sanga Mitra

Dependencies

This repository contains two independent R-based codebases with different software dependencies. Each codebase includes its own documentation describing the required R version, package dependencies, installation instructions, and workflow.

Please refer to the README file within each folder for detailed dependency information:

Deconvolution_Main_Code/

Deconvolution_Downstream_Analyses/

License preamble

Copyright © 2026 Bioinformatics and Integrative Data Science (BIRDS) Group, Indian Institute of Technology Madras.

The Deconvolution Project is open-source software released under the MIT License. You are free to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of this software, provided that the copyright notice and the MIT License are included in all copies or substantial portions of the software.

See the accompanying LICENSE file for the complete license terms.

Status

This repository accompanies a research study. The associated manuscript has been submitted for peer review.

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This repository contains code used to investigate the downstream effects of applying cell-type deconvolution methods to transcriptomic data

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