Article

DECODE: Deep learning-based common deconvolution framework for various omics data

2025-02-26

Abstract excerpt

<title>Abstract</title> <p>Deconvolution algorithm enables estimation of cell type abundances from tissue-level data, providing a crucial way for exploring plentiful cohort data at the cellular level. However, most deconvolution algorithms are specifically designed for single-omics data, thereby limiting their generalizability and scalability for multiomics data from different cohorts. A deconvolution algorithm a...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 60a88c83-a1e2-59d5-8d67-9d26e7677541
DOI: 10.21203/rs.3.rs-6004616/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

DECODE: Deep learning-based common deconvolution framework for various omics dataDOI 10.21203/rs.3.rs-6004616/v1Read

Deconvolution of omics data in Python with Deconomix – cellular compositions, cell-type specific gene regulation, and background contributionsSemantic proximity Read

Deep Learning Applications in Single-Cell Omics Data AnalysisSemantic proximity Read

Transferable spatial omics deconvolution with SpaRankSemantic proximity Read

DeMixSC: a deconvolution framework that uses single-cell sequencing plus a small benchmark dataset for improved analysis of cell-type ratios in complex tissue samplesSemantic proximity Read

ICTD: A semi-supervised cell type identification and deconvolution method for multi-omics dataSemantic proximity Read

Deep-learning-based cell composition analysis from tissue expression profilesSemantic proximity Read

MuSiC2: cell type deconvolution for multi-condition bulk RNA-seq dataSemantic proximity Read

Deep autoencoder for interpretable tissue-adaptive deconvolution and cell-type-specific gene analysisSemantic proximity Read

<i>imply</i> : improving cell-type deconvolution accuracy using personalized reference profilesSemantic proximity Read

CytoPro: A computational platform for accurate and robust assessment of cell contributions in bulk expression from diverse tissues and conditionsSemantic proximity Read

Bulk Tissue Cell Type Deconvolution with Multi-Subject Single-Cell Expression ReferenceSemantic proximity Read

SCDC: Bulk Gene Expression Deconvolution by Multiple Single-Cell RNA Sequencing ReferencesSemantic proximity Read