Article

swCAM: estimation of subtype-specific expressions in individual samples with unsupervised sample-wise deconvolution

2021-01-05

Abstract excerpt

<h4>Motivation</h4> Complex biological tissues are often a heterogeneous mixture of several molecularly distinct cell or tissue subtypes. Both subtype compositions and expressions in individual samples can vary across different biological states or conditions. Computational deconvolution aims to dissect patterns of bulk gene expression data into subtype compositions and subtype-specific expressions. Typically, ex...

Topics

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

Identifiers and source

Literature Corpus work: fffdff36-b427-592c-bd74-ec2b8ad3c316
DOI: 10.1101/2021.01.04.425315

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

swCAM: estimation of subtype-specific expressions in individual samples with unsupervised sample-wise deconvolutionDOI 10.1101/2021.01.04.425315Read

Systematic assessment of the biological impact of cellular deconvolution on downstream analyses of disease transcriptomesSemantic proximity Read

Improving Differential Expression and Survival Analyses with Sample Specific Compartment DeconvolutionSemantic proximity Read

A computational method for direct imputation of cell type-specific expression profiles and cellular compositions from bulk-tissue RNA-Seq in brain disordersSemantic proximity Read

Single-cell deconvolution of 3,000 post-mortem brain samples for eQTL and GWAS dissection in mental disordersSemantic proximity Read

Resolving malignant cell heterogeneity from bulk tumor RNA-seq data with CDStateSemantic proximity Read

Evaluating performance and applications of sample-wise cell deconvolution methods on human brain transcriptomic dataSemantic proximity Read

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

Cell-type specific inference from bulk RNA-sequencing data by integrating single cell reference profiles via EPIC-unmixSemantic proximity Read

Accurate estimation of cell composition in bulk expression through robust integration of single-cell informationSemantic proximity Read

Comprehensive evaluation of deconvolution methods for human brain gene expressionSemantic proximity Read

Efficient differential expression analysis of large-scale single cell transcriptomics data using dreamletSemantic proximity Read