Article

Cell type classification and discovery across diseases, technologies and tissues reveals conserved gene signatures and enables standardized single-cell readouts

2021-02-12

Abstract excerpt

Autoimmune diseases are a major cause of mortality1,2. Current treatments often yield severe insult to host tissue. It is hypothesized that improved therapies will target pathogenic cells selectively and thus reduce or eliminate severe side effects, and potentially induce robust immune tolerance3. However, it remains challenging to systematically identify which cellular phenotypes are present in cellular ensembles...

Topics

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

Identifiers and source

Literature Corpus work: d267121d-80c3-53b3-9f75-0e0446691d9e
DOI: 10.21203/rs.3.rs-199733/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Cell type classification and discovery across diseases, technologies and tissues reveals conserved gene signatures and enables standardized single-cell readoutsDOI 10.21203/rs.3.rs-199733/v1Read

Cell type classification and discovery across diseases, technologies and tissues reveals conserved gene signatures and enables standardized single-cell readoutsSemantic proximity Read

Moana: A robust and scalable cell type classification framework for single-cell RNA-Seq dataSemantic proximity Read

Explainable deep neural networks for predicting sample phenotypes from single-cell transcriptomicsSemantic proximity Read

scQuery: a web server for comparative analysis of single-cell RNA-seq dataSemantic proximity Read

CloudPred: Predicting Patient Phenotypes From Single-cell RNA-seq.Semantic proximity Read

Single-cell mapper (scMappR): using scRNA-seq to infer cell-type specificities of differentially expressed genesSemantic proximity Read

Robust identification of perturbed cell types in single-cell RNA-seq dataSemantic proximity Read

CTDP: Identifying cell types associated with disease phenotypes using scRNA-seq dataSemantic proximity Read

<i>Besca</i> , a single-cell transcriptomics analysis toolkit to accelerate translational researchSemantic proximity Read

scPanel: A tool for automatic identification of sparse gene panels for generalizable patient classification using scRNA-seq datasetsSemantic proximity Read

Genular: An Integrated Platform for Defining Cellular Identity and Function through Single-Cell Gene Expression and Multi-Domain Biological DataSemantic proximity Read

Deep scSTAR: leveraging deep learning for the extraction and enhancement of phenotype-associated features from single-cell RNA sequencing and spatial transcriptomics dataSemantic proximity Read