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GeneMarkeR: A Database and User Interface for scRNA-seq Marker Genes

Single-cell sequencing (scRNA-seq) has enabled researchers to study cellular heterogeneity. Accurate cell type identification is crucial for scRNA-seq analysis to be valid and robust. Marker genes, genes specific for one or a few cell types, can improve cell type classification; however, their speci...

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Detalles Bibliográficos
Autores principales: Paisley, Brianna M., Liu, Yunlong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8577352/
https://www.ncbi.nlm.nih.gov/pubmed/34764987
http://dx.doi.org/10.3389/fgene.2021.763431
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author Paisley, Brianna M.
Liu, Yunlong
author_facet Paisley, Brianna M.
Liu, Yunlong
author_sort Paisley, Brianna M.
collection PubMed
description Single-cell sequencing (scRNA-seq) has enabled researchers to study cellular heterogeneity. Accurate cell type identification is crucial for scRNA-seq analysis to be valid and robust. Marker genes, genes specific for one or a few cell types, can improve cell type classification; however, their specificity varies across species, samples, and cell subtypes. Current marker gene databases lack standardization, cell hierarchy consideration, sample diversity, and/or the flexibility for updates as new data become available. Most of these databases are derived from a single statistical analysis despite many such analyses scattered in the literature to identify marker genes from scRNA-seq data and pure cell populations. An R Shiny web tool called GeneMarkeR was developed for researchers to retrieve marker genes demonstrating cell type specificity across species, methodology and sample types based on a novel algorithm. The web tool facilitates online submission and interfaces with MySQL to ensure updatability. Furthermore, the tool incorporates reactive programming to enable researchers to retrieve standardized public data supporting the marker genes. GeneMarkeR currently hosts over 261,000 rows of standardized marker gene results from 25 studies across 21,012 unique genomic entities and 99 unique cell types mapped to hierarchical ontologies.
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spelling pubmed-85773522021-11-10 GeneMarkeR: A Database and User Interface for scRNA-seq Marker Genes Paisley, Brianna M. Liu, Yunlong Front Genet Genetics Single-cell sequencing (scRNA-seq) has enabled researchers to study cellular heterogeneity. Accurate cell type identification is crucial for scRNA-seq analysis to be valid and robust. Marker genes, genes specific for one or a few cell types, can improve cell type classification; however, their specificity varies across species, samples, and cell subtypes. Current marker gene databases lack standardization, cell hierarchy consideration, sample diversity, and/or the flexibility for updates as new data become available. Most of these databases are derived from a single statistical analysis despite many such analyses scattered in the literature to identify marker genes from scRNA-seq data and pure cell populations. An R Shiny web tool called GeneMarkeR was developed for researchers to retrieve marker genes demonstrating cell type specificity across species, methodology and sample types based on a novel algorithm. The web tool facilitates online submission and interfaces with MySQL to ensure updatability. Furthermore, the tool incorporates reactive programming to enable researchers to retrieve standardized public data supporting the marker genes. GeneMarkeR currently hosts over 261,000 rows of standardized marker gene results from 25 studies across 21,012 unique genomic entities and 99 unique cell types mapped to hierarchical ontologies. Frontiers Media S.A. 2021-10-26 /pmc/articles/PMC8577352/ /pubmed/34764987 http://dx.doi.org/10.3389/fgene.2021.763431 Text en Copyright © 2021 Paisley and Liu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Paisley, Brianna M.
Liu, Yunlong
GeneMarkeR: A Database and User Interface for scRNA-seq Marker Genes
title GeneMarkeR: A Database and User Interface for scRNA-seq Marker Genes
title_full GeneMarkeR: A Database and User Interface for scRNA-seq Marker Genes
title_fullStr GeneMarkeR: A Database and User Interface for scRNA-seq Marker Genes
title_full_unstemmed GeneMarkeR: A Database and User Interface for scRNA-seq Marker Genes
title_short GeneMarkeR: A Database and User Interface for scRNA-seq Marker Genes
title_sort genemarker: a database and user interface for scrna-seq marker genes
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8577352/
https://www.ncbi.nlm.nih.gov/pubmed/34764987
http://dx.doi.org/10.3389/fgene.2021.763431
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