TranscriptML

TranscriptML provides data preparation, model training, evaluation, and interpretation tools for RNA sequence-to-function models. It is designed for two common starting points:

• transcript-level measurements paired with annotated transcript sequences, modeled with Saluki; and

• MPRA measurements paired with one variable RNA insert per construct, modeled with LegNet.

Interpretation tools include single-nucleotide in silico mutagenesis (ISM), motif ablations, motif context scans, motif epistasis analyses, and Saluki-specific codon ISM. These analyses can expose learned regulatory sequence features as well as technical artifacts in the model or assay.

RiboNN support for translation measurements and RBPNet support for RBP binding measurements are planned but not yet implemented.

Start here

See Installation for the smallest install that covers your use case. The Usage guide walks through Saluki and MPRA projects from input tables through cross-validation and interpretation. Use the API reference reference when calling TranscriptML from Python.

Contents

• Installation
• Usage
  • Saluki Workflow
  • MPRA-LegNet Workflow
  • Other Useful Commands
• API reference
  • Data
  • Models
  • Training and evaluation
  • Interpretation
  • Plotting
  • Run setup