Article

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

2021-08-19

Abstract excerpt

Cells are the quanta unit of biology and their relative composition in a tissue is the prime driver of bulk tissue gene expression variation. When there is no cell information, deconvolution is an effective tool to achieve cell resolution, which provides important information for learning disease complexity and its interactions with treatments, drugs and/or the environment in a wide variety of contexts. Here we pr...

Topics

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

Identifiers and source

Literature Corpus work: f2fa1a79-8e35-5b07-846c-4cc12e6d48cf
DOI: 10.1101/2021.08.19.456930

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

CytoPro: A computational platform for accurate and robust assessment of cell contributions in bulk expression from diverse tissues and conditionsDOI 10.1101/2021.08.19.456930Read

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

ELITE: Expression deconvoLution using lInear optimizaTion in bulk transcriptomics mixturEsSemantic proximity Read

AutoGeneS: Automatic gene selection using multi-objective optimization for RNA-seq deconvolutionSemantic proximity Read

<i>multideconv</i> - an integrative pipeline for efficiently combining first and second generation cell type deconvolution resultsSemantic proximity Read

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

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

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

Bulk tissue cell type deconvolution with multi-subject single-cell expression referenceSemantic proximity Read

Estimating cell compositions and cell-type-specific expressions from GWAS data using invariant causal prediction, deep learning and regularized matrix completionSemantic proximity Read

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

Deconer: A comprehensive and systematic evaluation toolkit for reference-based cell type deconvolution algorithms using gene expression dataSemantic proximity Read

High-resolution reconstruction of cell-type specific transcriptional regulatory processes from bulk sequencing samplesSemantic proximity Read