Motivation While promoter methylation is associated with reinforcing fundamental tissue identities, the methylation status of distant enhancers was shown by genome-wide association studies to be a powerful determinant of cell-state and cancer. With recent availability of long reads that report on the methylation status of enhancer–promoter pairs on the same molecule, we hypothesized that probing these pairs on the single-molecule level may serve the basis for detection of rare cancerous transformations in a given cell population. We explore various analysis approaches for deconvolving cell-type mixtures based on their genome-wide enhancer–promoter methylation profiles. Results To evaluate our hypothesis we examine long-read optical methylome data for the GM12878 cell line and myoblast cell lines from two donors. We identified over 100 000 enhancer–promoter pairs that co-exist on at least 30 individual DNA molecules. We developed a detailed methodology for mixture deconvolution and applied it to estimate the proportional cell compositions in synthetic mixtures. Analysis of promoter methylation, as well as enhancer–promoter pairwise methylation, resulted in very accurate estimates. In addition, we show that pairwise methylation analysis can be generalized from deconvolving different cell types to subtle scenarios where one wishes to resolve different cell populations of the same cell-type. Availability and implementation The code used in this work to analyze single-molecule Bionano Genomics optical maps is available via the GitHub repository https://github.com/ebensteinLab/Single_molecule_methylation_in_EP.
MotivationWhile promoter methylation is associated with reinforcing fundamental tissue identities, the methylation status of distant enhancers was shown by genome-wide association studies to be a powerful determinant of cell-state and cancer. With recent availability of long-reads that report on the methylation status of enhancer-promoter pairs on the same molecule, we hypothesized that probing these pairs on the single-molecule level may serve the basis for detection of rare cancerous transformations in a given cell population. We explore various analysis approaches for deconvolving cell-type mixtures based on their genome-wide enhancer-promoter methylation profiles.ResultsTo evaluate our hypothesis we examine long-read optical methylome data for the GM12787 cell line and myoblast cell lines from two donors. We identified over 100,000 enhancer-promoter pairs that co-exist on at least 30 individual DNA molecules per pair. We developed a detailed methodology for mixture deconvolution and applied it to estimate the proportional cell compositions in synthetic mixtures based on analyzing their enhancer-promoter pairwise methylation. We found our methodology to lead to very accurate estimates, outperforming our promoter-based deconvolutions. Moreover, we show that it can be generalized from deconvolving different cell types to subtle scenarios where one wishes to deconvolve different cell populations of the same cell-type.AvailabilityThe code used in this work to analyze single-molecule Bionano Genomics optical maps is available via the GitHub repository https://github.com/ebensteinLab/Single_molecule_methylation_in_EP.Contactuv@post.tau.ac.il (Y.E), roded@tauex.tau.ac.il (R.S)
We show that the following problem is decidable: given expressions E 1 and E 2 constructed from variables by the regular operations and shuffle, is the identity E 1 = E 2 true for all instantiations of its variables by strings? Our proof uses the notations developed in the causal approach to concurrency. As a byproduct we obtain decidability of similar equivalence for other formalisms. In particular, we prove decidability of split equivalence for Petri nets. Our paper also provides an alternative proof for a characterization of split equivalence recently given by W.Vogler.
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