{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T14:15:35Z","timestamp":1778163335309,"version":"3.51.4"},"reference-count":18,"publisher":"Public Library of Science (PLoS)","issue":"12","license":[{"start":{"date-parts":[[2024,12,12]],"date-time":"2024-12-12T00:00:00Z","timestamp":1733961600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100007028","name":"Leona M. and Harry B. Helmsley Charitable Trust","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007028","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000143","name":"Division of Computing and Communication Foundations","doi-asserted-by":"publisher","award":["CCF2007029"],"award-info":[{"award-number":["CCF2007029"]}],"id":[{"id":"10.13039\/100000143","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>When analyzing scRNA-seq data containing heterogeneous cell populations, an important task is to select informative marker genes to distinguish various cell clusters and annotate the clusters with biologically meaningful cell types. In existing analysis methods and pipelines, marker genes are typically identified using a one-vs-all strategy, examining differential expression between one cell cluster versus the combination of all other cell clusters. However, this strategy applied to cell clusters belonging to closely related cell types often generates overlapping marker genes, which capture the common signature of closely related cell clusters but provide limited information for distinguishing them. To address the limitations of the one-vs-all strategy, we propose a hierarchical marker gene selection strategy that groups similar cell clusters and selects marker genes in a hierarchical manner. This strategy is able to improve the accuracy and interpretability of cell type identification in single-cell RNA-seq data.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1012643","type":"journal-article","created":{"date-parts":[[2024,12,12]],"date-time":"2024-12-12T18:22:58Z","timestamp":1734027778000},"page":"e1012643","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":4,"title":["Hierarchical marker genes selection in scRNA-seq analysis"],"prefix":"10.1371","volume":"20","author":[{"given":"Yutong","family":"Sun","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3256-0734","authenticated-orcid":true,"given":"Peng","family":"Qiu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"340","published-online":{"date-parts":[[2024,12,12]]},"reference":[{"issue":"5","key":"pcbi.1012643.ref001","doi-asserted-by":"crossref","first-page":"1202","DOI":"10.1016\/j.cell.2015.05.002","article-title":"Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets","volume":"161","author":"EZ Macosko","year":"2015","journal-title":"Cell"},{"issue":"1","key":"pcbi.1012643.ref002","doi-asserted-by":"crossref","first-page":"14049","DOI":"10.1038\/ncomms14049","article-title":"Massively parallel digital transcriptional profiling of single cells","volume":"8","author":"GX Zheng","year":"2017","journal-title":"Nature communications"},{"issue":"10","key":"pcbi.1012643.ref003","doi-asserted-by":"crossref","first-page":"e9005","DOI":"10.15252\/msb.20199005","article-title":"Combinatorial prediction of marker panels from single-cell transcriptomic data","volume":"15","author":"C Delaney","year":"2019","journal-title":"Molecular systems biology"},{"issue":"7","key":"pcbi.1012643.ref004","doi-asserted-by":"crossref","first-page":"1888","DOI":"10.1016\/j.cell.2019.05.031","article-title":"Comprehensive integration of single-cell data","volume":"177","author":"T Stuart","year":"2019","journal-title":"Cell"},{"issue":"4","key":"pcbi.1012643.ref005","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1038\/nbt.2859","article-title":"The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells","volume":"32","author":"C Trapnell","year":"2014","journal-title":"Nature biotechnology"},{"issue":"2","key":"pcbi.1012643.ref006","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1038\/s41590-018-0276-y","article-title":"Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage","volume":"20","author":"D Aran","year":"2019","journal-title":"Nature immunology"},{"issue":"1","key":"pcbi.1012643.ref007","doi-asserted-by":"crossref","first-page":"1186","DOI":"10.1038\/s41467-021-21453-4","article-title":"Optimal marker gene selection for cell type discrimination in single cell analyses","volume":"12","author":"B Dumitrascu","year":"2021","journal-title":"Nature communications"},{"key":"pcbi.1012643.ref008","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12859-020-03641-z","article-title":"A rank-based marker selection method for high throughput scRNA-seq data","volume":"21","author":"AH Vargo","year":"2020","journal-title":"BMC bioinformatics"},{"issue":"5","key":"pcbi.1012643.ref009","doi-asserted-by":"crossref","first-page":"483","DOI":"10.1038\/nmeth.4236","article-title":"SC3: consensus clustering of single-cell RNA-seq data","volume":"14","author":"VY Kiselev","year":"2017","journal-title":"Nature methods"},{"issue":"10","key":"pcbi.1012643.ref010","doi-asserted-by":"crossref","first-page":"e1007445","DOI":"10.1371\/journal.pcbi.1007445","article-title":"SCMarker: ab initio marker selection for single cell transcriptome profiling","volume":"15","author":"F Wang","year":"2019","journal-title":"PLoS computational biology"},{"issue":"8","key":"pcbi.1012643.ref011","doi-asserted-by":"crossref","first-page":"2474","DOI":"10.1093\/bioinformatics\/btz936","article-title":"scTIM: seeking cell-type-indicative marker from single cell RNA-seq data by consensus optimization","volume":"36","author":"Z Feng","year":"2020","journal-title":"Bioinformatics"},{"key":"pcbi.1012643.ref012","unstructured":"Lab S. pbmc3k.SeuratData: 3k PBMCs from 10X Genomics; 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