Nature Communications · 2018 · 211 citations · 12 references
Life SciencesGeneticsMolecular BiologyEpigeneticsEpigenomicsGenomicsDna Methylation ProfilingEpigenomic Data AnalysisEpigenomic ProfilingSingle-cell AnalysisSingle-cell EpigenomicsSingle-cell GenomicsGenome-wide Methylation AnalysisLibrary Complexity OptimizationReprogrammingSingle-cell Dna MethylationSingle-cell Dna Methylation ProfilingSingle-cell Dna SequencingSingle-cell Epigenomic ProfilingSingle-cell Methylation Analysis
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.
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