Sheng Li

TL;DR: An R package that rapidly analyzes genome-wide cytosine epigenetic profiles from high-throughput methylation and Hydroxymethylation sequencing experiments is described, which includes functions for clustering, sample quality visualization, differential methylation analysis and annotation features, thus automating and simplifying many of the steps for discerning statistically significant bases or regions of DNAmethylation.

TL;DR: The complete SEQC data sets, comprising >100 billion reads, provide unique resources for evaluating RNA-seq analyses for clinical and regulatory settings, and measurement performance depends on the platform and data analysis pipeline, and variation is large for transcript-level profiling.

TL;DR: Loss of Asxl1 results in myelodysplastic syndrome, whereas concomitant deletion of Tet2 restores HSC self-renewal and triggers a more severe disease phenotype distinct from that seen in single-gene knockout mice.

TL;DR: It is observed that epigenetic allele burden is linked to inferior outcome and varies considerably during disease progression, and genetic and epigenetic heterogeneity can occur with distinct kinetics likely to affect the biological and clinical features of tumors.

TL;DR: Both labile and permanent modifications, from simple methylation to complex transcript alteration (RNA editing and intron retention) are examined; the models for their processing are detailed; and remaining questions in the field of the epitranscriptome are highlighted.