Skip to content

FiberHMM v2.0.0

Choose a tag to compare

View all tags
@mtcicero26 mtcicero26 released this 22 Feb 21:05
· 552 commits to main since this release
v2.0.0
34a2d4b
This commit was created on GitHub.com and signed with GitHub’s verified signature.
GPG key ID: B5690EEEBB952194
Verified
Learn about vigilant mode.

Complete rewrite of FiberHMM as a proper Python package.

What's New

  • Python package: pip install fiberhmm with CLI entry points (fiberhmm-apply, fiberhmm-train, fiberhmm-probs, fiberhmm-extract, fiberhmm-utils)
  • Native HMM: No hmmlearn dependency; optional Numba JIT for ~10x speedup
  • Region-parallel processing: Scales linearly with cores (-c 8)
  • Fibertools-compatible output: Tagged BAM with ns/nl/as/al tags
  • Pre-trained models: Hia5 (PacBio + Nanopore), DddA (PacBio), DddB (Nanopore)
  • Consolidated utilities: fiberhmm-utils with convert, inspect, transfer, adjust subcommands
  • JSON model format: Portable, human-readable; legacy pickle/NPZ still supported for loading

Pre-trained Models

Model Enzyme Platform Mode
hia5_pacbio.json Hia5 (m6A) PacBio pacbio-fiber
hia5_nanopore.json Hia5 (m6A) Nanopore nanopore-fiber
ddda_pacbio.json DddA (deamination) PacBio daf
dddb_nanopore.json DddB (deamination) Nanopore daf

Quick Start

pip install fiberhmm

# Call footprints with a pre-trained model
fiberhmm-apply -i experiment.bam -m models/hia5_pacbio.json -o output/ -c 8

See the README for full documentation.

Assets 2
Loading