Article

A statistical framework for the robust detection of hidden variation in single cell transcriptomes

2017-06-18

Abstract excerpt

Single cell RNA-sequencing (scRNA-seq) precisely characterize gene expression levels and dissect variation in expression associated with the state (technical or biological) and the type of the cell, which is averaged out in bulk measurements. Multiple and correlated sources contribute to gene expression variation in single cells, which makes their estimation difficult with the existing methods developed for bulk m...

Topics

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

Identifiers and source

Literature Corpus work: 9286de01-e2b1-50a9-bcae-ad4c24fc2fee
DOI: 10.1101/151217

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

A statistical framework for the robust detection of hidden variation in single cell transcriptomesDOI 10.1101/151217Read

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

Single-Cell Heterogeneity Analysis and CRISPR Screen Identify Key β-Cell-Specific Disease GenesSemantic proximity Read

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

Extent, heritability, and functional relevance of single cell expression variability in highly homogeneous populations of human cellsSemantic proximity Read

Isolating structured salient variations in single-cell transcriptomic data with StrastiveVISemantic proximity Read

Varying-Censoring Aware Matrix Factorization for Single Cell RNA-SequencingSemantic proximity Read

A robust model for cell type-specific interindividual variation in single-cell RNA sequencing dataSemantic proximity Read

Lessons from single-cell RNA sequencing of human isletsSemantic proximity Read

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

Interpretable single-cell factor decomposition using sciREDSemantic proximity Read

Harmonizing Heterogeneous Single-cell Gene Expression Data with Individual-level Covariate InformationSemantic proximity Read

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