Article

Probabilistic cell type assignment of single-cell transcriptomic data reveals spatiotemporal microenvironment dynamics in human cancers

2019-01-16

Abstract excerpt

Single-cell RNA sequencing (scRNA-seq) has transformed biomedical research, enabling decomposition of complex tissues into disaggregated, functionally distinct cell types. For many applications, investigators wish to identify cell types with known marker genes. Typically, such cell type assignments are performed through unsupervised clustering followed by manual annotation based on these marker genes, or via "mapp...

Topics

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

Identifiers and source

Literature Corpus work: 2cafa129-da14-5e23-9afc-684e21a4a0be
DOI: 10.1101/521914

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Probabilistic cell type assignment of single-cell transcriptomic data reveals spatiotemporal microenvironment dynamics in human cancersDOI 10.1101/521914Read

Probabilistic cell-type assignment of single-cell RNA-seq for tumor microenvironment profilingSemantic proximity Read

Unveiling Gene Modules at Atlas Scale through Hierarchical Clustering of Single-Cell DataSemantic proximity Read

scTransMIL Bridges Patient-Level Phenotypes and Single-Cell Transcriptomics for Cancer Screening and Heterogeneity InferenceSemantic proximity Read

Bayesian cell-type deconvolution and gene expression inference reveals tumor-microenvironment interactionsSemantic proximity Read

CellMeSH: Probabilistic Cell-Type Identification Using Indexed LiteratureSemantic proximity Read

Highly accurate estimation of cell type abundance in bulk tissues based on single-cell reference and domain adaptive matchingSemantic proximity Read

ASURAT: functional annotation-driven unsupervised clustering of single-cell transcriptomesSemantic proximity Read

Fully-automated and ultra-fast cell-type identification using specific marker combinations from single-cell transcriptomic dataSemantic proximity Read

Joint cell type identification in spatial transcriptomics and single-cell RNA sequencing dataSemantic proximity Read

Sample-level modeling of single-cell data at scale with <i>tinydenseR</i>Semantic proximity Read

scMoE: single-cell mixture of experts for learning hierarchical, cell-type-specific, and interpretable representations from heterogeneous scRNA-seq dataSemantic proximity Read

SCIPAC: quantitative estimation of cell-phenotype associations.Semantic proximity Read