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m6a-clip

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Map N6-methyladenosine (m6A) RNA modifications at single-nucleotide resolution using miCLIP (Linder 2015), miCLIP2 + m6Aboost machine learning (Kortel 2021), GLORI (Liu 2023, antibody-free chemical conversion), DART-seq (Meyer 2019, APOBEC1-YTH fusion), m6Anet (nanopore direct RNA), or MeRIP-seq with calibration. Use when distinguishing antibody-based from antibody-free m6A detection methods, applying the DRACH motif constraint, reconciling cross-method disagreements (DART 44% in DRACH vs GLORI), or detecting m6Am at the cap.

When to use

• Map m6A modifications at single-nucleotide resolution
• Distinguishing antibody-based from antibody-free m6A detection methods
• Applying the DRACH motif constraint
• Reconciling cross-method disagreements
• Detecting m6Am at the cap
• miCLIP2 pipeline analysis
• GLORI-tools Python pipeline
• m6Anet nanopore inference

When not to use

• MeRIP-seq peak calling for low-resolution m6A
• Postprocessing only calibration without primary data

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