Single-Cell RNA-Sequencing

Single-Cell RNA-Sequencing

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1-11 of 11 ARTICLES
 in 
https://doi.org/10.12688/f1000research.168556.1
Research Article metrics AWAITING PEER REVIEW
Single-cell RNA sequencing of cerebrospinal fluid reveals the expansion of innate lymphoid cells with upregulated transposable elements in multiple sclerosis
[version 1; peer review: awaiting peer review]
Pouria Mosaddeghi, Mitra Farahmandnejad, Mohammad M. Zarshenas
Peer Reviewers Invited
  • Funder
  • Shiraz University of Medical Sciences
PUBLISHED 10 Oct 2025
https://doi.org/10.12688/f1000research.74416.2
Software Tool Article metrics
Revised
BASiCS workflow: a step-by-step analysis of expression variability using single cell RNA sequencing data
[version 2; peer review: 1 approved, 2 approved with reservations]
Alan O'Callaghan, Nils Eling, John C. Marioni, Catalina A. Vallejos
Peer Reviewers Oliver M. Crook; Andrew McDavid; Michel S Naslavsky
  • Funders
  • Cancer Research UK
  • University of Edinburgh
  • European Molecular Biology Laboratory
LATEST VERSION PUBLISHED 07 May 2024
https://doi.org/10.12688/f1000research.130623.2
Research Article metrics
Revised
Thinking process templates for constructing data stories with SCDNEY
[version 2; peer review: 2 approved]
Yue Cao, Andy Tran, Hani Kim, Nick Robertson, Yingxin Lin, Marni Torkel, Pengyi Yang, Ellis Patrick, Shila Ghazanfar, Jean Yang
Peer Reviewers Jun Li; Kelly Street
  • Funders
  • University of Sydney Postgraduate Award Stipend Scholarship
  • A National Health and Medical Research Council (NHMRC) Investigator Grant
  • the AIR@innoHK programme of the Innovation and Technology Commission of Hong Kong
  • Australian Research Council Discovery Early Career Researcher Awards
  • Research Training Program Tuition Fee Offset and Stipend Scholarship
LATEST VERSION PUBLISHED 15 Dec 2023
https://doi.org/10.12688/f1000research.134078.2
Method Article metrics
Revised
Unraveling the timeline of gene expression: A pseudotemporal trajectory analysis of single-cell RNA sequencing data
[version 2; peer review: 2 approved, 1 approved with reservations]
Jinming Cheng, Gordon K. Smyth, Yunshun Chen
Peer Reviewers Michael D Morgan; Koen Van den berge; Anna Alemany, Xuan Quy Nguyen and Noëlle Dommann
  • Funders
  • National Health and Medical Research Council
  • Chan Zuckerberg Initiative
  • Medical Research Future Fund
LATEST VERSION PUBLISHED 10 Nov 2023
https://doi.org/10.12688/f1000research.126243.2
Review metrics
Revised
Integration of single-cell RNA sequencing and spatial transcriptomics to reveal the glioblastoma heterogeneity
[version 2; peer review: 3 approved]
Adrian Perdyan, Urszula Lawrynowicz, Monika Horbacz, Bozena Kaminska, Jakub Mieczkowski
Peer Reviewers Dieter Henrik Heiland; Theo Mantamadiotis; Georges Nemer
  • Funders
  • Fundacja na rzecz Nauki Polskiej
  • Narodowe Centrum Nauki
  • National Science Centre
LATEST VERSION PUBLISHED 09 Aug 2023
https://doi.org/10.12688/f1000research.125579.1
Research Article metrics
Cell-type classification of cancer single-cell RNA-seq data using the Subsemble ensemble-based machine learning classifier
[version 1; peer review: 3 approved with reservations]
David Chen, Parisa Shooshtari
Peer Reviewers Saskia Freytag; Yue Cao; Zhixiang Ren
  • Funders
  • Children's Health Research Institute
  • Ontario Institute for Cancer Research
  • Natural Sciences and Engineering Research Council of Canada
  • NSERC Undergraduate Student Research Award
PUBLISHED 14 Apr 2023
https://doi.org/10.12688/f1000research.54864.2
Research Article metrics
Revised
The need to reassess single-cell RNA sequencing datasets: the importance of biological sample processing
[version 2; peer review: 2 approved]
Alex M. Ascensión, Marcos J. Araúzo-Bravo, Ander Izeta
Peer Reviewers Xiao Long and Zhujun Li; (Jo) Huiqing Zhou
  • Funders
  • Hezkuntza, Hizkuntza Politika Eta Kultura Saila, Eusko Jaurlaritza
  • Instituto de Salud Carlos III
  • Horizon 2020
  • European Regional Development Fund
LATEST VERSION PUBLISHED 08 Mar 2022
https://doi.org/10.12688/f1000research.24163.2
Method Article metrics
Revised
Spatial mapping of single cells in the Drosophila embryo from transcriptomic data based on topological consistency
[version 2; peer review: 2 approved]
Maryam Zand, Jianhua Ruan
Peer Reviewers Tianci Song and Rui Kuang; Adi Tarca
  • Funders
  • National Institutes of Health
  • National Science Foundation
LATEST VERSION PUBLISHED 09 Feb 2021
https://doi.org/10.12688/f1000research.22969.2
Software Tool Article metrics
Revised
clustifyr: an R package for automated single-cell RNA sequencing cluster classification
[version 2; peer review: 2 approved]
Rui Fu, Austin E. Gillen, Ryan M. Sheridan, Chengzhe Tian, Michelle Daya, Yue Hao, Jay R. Hesselberth, Kent A. Riemondy
Peer Reviewers Keegan Korthauer; Kamil Slowikowski
  • Funders
  • University of Colorado School of Medicine
  • National Institute of General Medical Sciences
LATEST VERSION PUBLISHED 16 Jul 2020
https://doi.org/10.12688/f1000research.18490.3
Research Article metrics
Revised
Evaluation of methods to assign cell type labels to cell clusters from single-cell RNA-sequencing data
[version 3; peer review: 2 approved, 1 approved with reservations]
J. Javier Diaz-Mejia, Elaine C. Meng, Alexander R. Pico, Sonya A. MacParland, Troy Ketela, Trevor J. Pugh, Gary D. Bader, John H. Morris
Peer Reviewers Saskia Freytag; Jimmy Tsz Hang Lee and Tallulah Andrews; Lindsay Cowell
  • Funders
  • National Resource for Network Biology
  • Chan Zuckerberg Initiative
LATEST VERSION PUBLISHED 14 Oct 2019
https://doi.org/10.12688/f1000research.11290.1
Research Article metrics
Gene length and detection bias in single cell RNA sequencing protocols
[version 1; peer review: 4 approved]
Belinda Phipson, Luke Zappia, Alicia Oshlack
Peer Reviewers Charlotte Soneson;  Samuel W. Lukowski; Wolfgang Huber; Sam Buckberry and Timothy Stuart
  • Funders
  • National Health and Medical Research Council
  • Australian Federal Government
PUBLISHED 28 Apr 2017
1-11 of 11 ARTICLES
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