Article

Fine-grained deconvolution of cell-type effects from human bulk brain data using a large single-nucleus RNA sequencing based reference panel

2022-06-24

Abstract excerpt

Brain disorders are leading causes of disability worldwide. Gene expression studies provide promising opportunities to better understand their etiology. When studying bulk tissue, cellular diversity may cause many genes that are differentially expressed in cases and controls to remain undetected. Furthermore, identifying the specific cell-types from which association signals originate is key to formulating refined...

Topics

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

Identifiers and source

Literature Corpus work: fa454649-9d03-5817-85fd-1240328c672a
DOI: 10.1101/2022.06.23.497397

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Fine-grained deconvolution of cell-type effects from human bulk brain data using a large single-nucleus RNA sequencing based reference panelDOI 10.1101/2022.06.23.497397Read

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

Single-nucleus transcriptome-wide association study of human brain disordersSemantic 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

Cell-type deconvolution of bulk-blood RNA-seq reveals biological insights into neuropsychiatric disorders.Semantic proximity Read

Cell type deconvolution of bulk blood RNA-Seq to reveal biological insights of neuropsychiatric disordersSemantic proximity Read

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

High cell-type specificity of eQTLs revealed by single-nucleus analyses of brain and bloodSemantic proximity Read

Deconvolving the contributions of cell-type heterogeneity on cortical gene expression.Semantic proximity Read

Single-cell genomics and regulatory networks for 388 human brainsSemantic proximity Read

Bayesian estimation of cell-type-specific gene expression per bulk sample with prior derived from single-cell dataSemantic proximity Read

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

Single-Nucleus Atlas of Cell-Type Specific Genetic Regulation in the Human BrainSemantic proximity Read