Scm6A: A fast and low-cost method for quantifying m6A modifications at the single-cell level
Yueqi Li,
Jingyi Li,
Wenxing Li
et al.
Abstract:It is widely accepted that m6A exhibits significant intercellular specificity, which poses challenges for its detection using existing m6A quantitative methods. In this study, we introduce Scm6A, a machine learning-based approach for single-cell m6A quantification. Scm6A leverages input features derived from the expression levels of m6Atransregulators andcissequence features, and found that Scm6A offers remarkable prediction efficiency and reliability. To further validate the robustness and precision of Scm6A,… Show more
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