{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Luo C"],"funding":["NIMH NIH HHS","NHGRI NIH HHS","U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (NHGRI)","U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute","U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH)","U.S. Department of Health & Human Services | NIH | National Institute of Mental Health"],"pagination":["3824"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC6147798"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["9(1)"],"pubmed_abstract":["Single-cell DNA methylome profiling has enabled the study of epigenomic heterogeneity in complex tissues and during cellular reprogramming. However, broader applications of the method have been impeded by the modest quality of sequencing libraries. Here we report snmC-seq2, which provides improved read mapping, reduced artifactual reads, enhanced throughput, as well as increased library complexity and coverage uniformity compared to snmC-seq. snmC-seq2 is an efficient strategy suited for large-scale single-cell epigenomic studies."],"journal":["Nature communications"],"pubmed_title":["Robust single-cell DNA methylome profiling with snmC-seq2."],"pmcid":["PMC6147798"],"funding_grant_id":["R21 HG009274","R21 MH112161","5U01MH105985","U01 MH105985","1R21HG009274","5R21MH112161","U19 MH114831"],"pubmed_authors":["Bui B","Behrens MM","Luo C","Rivkin A","Lucero J","Castanon R","Kurihara L","Nery JR","Fitzpatrick C","O'Connor C","Van Eden ME","Ecker JR","Mash DC","Ruga S","Davis DA","Zhou J","Sandoval JP","Pinto-Duarte A"],"additional_accession":[]},"is_claimable":false,"name":"Robust single-cell DNA methylome profiling with snmC-seq2.","description":"Single-cell DNA methylome profiling has enabled the study of epigenomic heterogeneity in complex tissues and during cellular reprogramming. However, broader applications of the method have been impeded by the modest quality of sequencing libraries. Here we report snmC-seq2, which provides improved read mapping, reduced artifactual reads, enhanced throughput, as well as increased library complexity and coverage uniformity compared to snmC-seq. snmC-seq2 is an efficient strategy suited for large-scale single-cell epigenomic studies.","dates":{"release":"2018-01-01T00:00:00Z","publication":"2018 Sep","modification":"2026-05-05T23:27:46.306Z","creation":"2019-03-26T23:57:24Z"},"accession":"S-EPMC6147798","cross_references":{"pubmed":["30237449"],"doi":["10.1038/s41467-018-06355-2"]}}