{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T20:34:50Z","timestamp":1772138090576,"version":"3.50.1"},"reference-count":40,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2018,7,25]],"date-time":"2018-07-25T00:00:00Z","timestamp":1532476800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000265","name":"UK Medical Research Council","doi-asserted-by":"crossref","award":["MC_UU_00002\/1"],"award-info":[{"award-number":["MC_UU_00002\/1"]}],"id":[{"id":"10.13039\/501100000265","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,2,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>A number of pseudotime methods have provided point estimates of the ordering of cells for scRNA-seq data. A still limited number of methods also model the uncertainty of the pseudotime estimate. However, there is still a need for a method to sample from complicated and multi-modal distributions of orders, and to estimate changes in the amount of the uncertainty of the order during the course of a biological development, as this can support the selection of suitable cells for the clustering of genes or for network inference.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>In applications to scRNA-seq data we demonstrate the potential of GPseudoRank to sample from complex and multi-modal posterior distributions and to identify phases of lower and higher pseudotime uncertainty during a biological process. GPseudoRank also correctly identifies cells precocious in their antiviral response and links uncertainty in the ordering to metastable states. A variant of the method extends the advantages of Bayesian modelling and MCMC to large droplet-based scRNA-seq datasets.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>Our method is available on github: https:\/\/github.com\/magStra\/GPseudoRank.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Supplementary information<\/jats:title>\n                    <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/bty664","type":"journal-article","created":{"date-parts":[[2018,7,24]],"date-time":"2018-07-24T07:13:15Z","timestamp":1532416395000},"page":"611-618","source":"Crossref","is-referenced-by-count":12,"title":["GPseudoRank: a permutation sampler for single cell orderings"],"prefix":"10.1093","volume":"35","author":[{"given":"Magdalena E","family":"Strau\u00df","sequence":"first","affiliation":[{"name":"MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John E","family":"Reid","sequence":"additional","affiliation":[{"name":"MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK"},{"name":"Alan Turing Institute, London, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lorenz","family":"Wernisch","sequence":"additional","affiliation":[{"name":"MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2018,7,25]]},"reference":[{"key":"2023051510551944600_bty664-B1","first-page":"bty533","article-title":"GrandPrix: scaling up the Bayesian GPLVM for single-cell data","author":"Ahmed","year":"2018","journal-title":"Bioinformatics"},{"key":"2023051510551944600_bty664-B2","doi-asserted-by":"crossref","first-page":"R106.","DOI":"10.1186\/gb-2010-11-10-r106","article-title":"Differential expression analysis for sequence count data","volume":"11","author":"Anders","year":"2010","journal-title":"Genome Biol"},{"key":"2023051510551944600_bty664-B3","doi-asserted-by":"crossref","first-page":"1241","DOI":"10.1093\/bioinformatics\/btv715","article-title":"destiny: diffusion maps for large-scale single-cell data in R","volume":"32","author":"Angerer","year":"2016","journal-title":"Bioinformatics"},{"key":"2023051510551944600_bty664-B4","doi-asserted-by":"crossref","first-page":"714","DOI":"10.1016\/j.cell.2014.04.005","article-title":"Single-cell trajectory detection uncovers progression and regulatory coordination in human B cell development","volume":"157","author":"Bendall","year":"2014","journal-title":"Cell"},{"key":"2023051510551944600_bty664-B5","volume-title":"Modern Multidimensional Scaling: Theory and Applications","author":"Borg","year":"2005","edition":"2"},{"key":"2023051510551944600_bty664-B6","doi-asserted-by":"crossref","first-page":"1093","DOI":"10.1038\/nmeth.2645","article-title":"Accounting for technical noise in single-cell RNA-seq experiments","volume":"10","author":"Brennecke","year":"2013","journal-title":"Nat. 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