{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T20:33:35Z","timestamp":1772138015923,"version":"3.50.1"},"reference-count":49,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2022,12,23]],"date-time":"2022-12-23T00:00:00Z","timestamp":1671753600000},"content-version":"vor","delay-in-days":1,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01MH113005"],"award-info":[{"award-number":["R01MH113005"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01LM012736"],"award-info":[{"award-number":["R01LM012736"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,1,19]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Single-cell assay for transposase accessible chromatin using sequencing (scATAC-seq) is a valuable resource to learn cis-regulatory elements such as cell-type specific enhancers and transcription factor binding sites. However, cell-type identification of scATAC-seq data is known to be challenging due to the heterogeneity derived from different protocols and the high dropout rate.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>In this study, we perform a systematic comparison of seven scATAC-seq datasets of mouse brain to benchmark the efficacy of neuronal cell-type annotation from gene sets. We find that redundant marker genes give a dramatic improvement for a sparse scATAC-seq annotation across the data collected from different studies. Interestingly, simple aggregation of such marker genes achieves performance comparable or higher than that of machine-learning classifiers, suggesting its potential for downstream applications. Based on our results, we reannotated all scATAC-seq data for detailed cell types using robust marker genes. Their meta scATAC-seq profiles are publicly available at https:\/\/gillisweb.cshl.edu\/Meta_scATAC. Furthermore, we trained a deep neural network to predict chromatin accessibility from only DNA sequence and identified key motifs enriched for each neuronal subtype. Those predicted profiles are visualized together in our database as a valuable resource to explore cell-type specific epigenetic regulation in a sequence-dependent and -independent manner.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bib\/bbac541","type":"journal-article","created":{"date-parts":[[2022,11,16]],"date-time":"2022-11-16T19:02:42Z","timestamp":1668625362000},"source":"Crossref","is-referenced-by-count":3,"title":["Learning single-cell chromatin accessibility profiles using meta-analytic marker genes"],"prefix":"10.1093","volume":"24","author":[{"given":"Risa Karakida","family":"Kawaguchi","sequence":"first","affiliation":[{"name":"Cold Spring Harbor Laboratory , Cold Spring Harbor 11724 , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ziqi","family":"Tang","sequence":"additional","affiliation":[{"name":"Cold Spring Harbor Laboratory , Cold Spring Harbor 11724 , 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Harbor 11724 , USA"},{"name":"Department of Physiology and Donnelly Centre for Cellular & Biomolecular Research Department, University of Toronto , Ontario M5S 3E1 , Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2022,12,22]]},"reference":[{"issue":"12","key":"2023011917134126700_ref2","doi-asserted-by":"crossref","first-page":"1213","DOI":"10.1038\/nmeth.2688","article-title":"Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position","volume":"10","author":"Buenrostro","year":"2013","journal-title":"Nat Methods"},{"issue":"6413","key":"2023011917134126700_ref3","doi-asserted-by":"crossref","first-page":"415.11","DOI":"10.1126\/science.362.6413.415-k","article-title":"The chromatin accessibility landscape of primary human cancers","volume":"362","author":"Ryan 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