v2.2.1

Added

• tandem: add CRAM input support with optional reference FASTA for alignment reading.
• tandem: support gzipped BED region inputs.

Changed

• Stopped building medaka-cpu pypi packages.
• Upgraded pyabpoa to version 1.5.6.
• tandem: fail fast on invalid inputs.
• Upgraded bundled HTSlib from 1.14 to 1.20.
• Updated build environment for arm wheels from manylinux2014 to manylinux_2_28.

Fixed

• The newly added -p prefix option to medaka_consensus was not correctly recognized.
• Save optimiser state in corresponding training folder.
• Training with --model pointing to a model archive now correctly loads the weights
  for the model rather than just creating a model with the same parameters but random
  weights.
• Move some inference options into correct parser section.
• Corrected learning-rate schedule for samples_per_training_epoch.
• Turn off scheduler update during validation.
• Fix command-line parsing so schedule is off by default.
• Prevent empty columns from potentially appearing in read-level features by allowing
  the insertion of reads whose alignment started while there was no available rows in
  the feature tensor.

v2.2.0

Added

• Python 3.13 support.
• medaka_consensus now has a -p <prefix> option to set the prefix for
  output consensus file (rather than always being consensus).

Fixed

• Issue where samtools version detection would stumble on meta-information
  lines in some builds of samtools.

Removed

• Python 3.9 support (EOL).

Changed

• medaka features fails if encoder expects dwells but data does not contain
  move tables, or warns if available move tables are not being used.
• During training, warning is output if model is not using available dwell
  information.
• Make more of an attempt to set threading appropriately for differing
  behaviours of pytorch and oneDNN builds.
• Replace read level features 3-dimensional tensor with structured numpy array
  for clarity and easier extension.

v2.1.1

Added

• Python 3.12 support

Fixed

• Issue with checking for the presence of dwell information in fastq files.

Changed

• Behaviour of medaka_consensus with --bacteria option: if the basecaller model cannot
  be parsed or is not compatible with the bacterial polishing model, exit with an error instead of
  falling back to default model.
• Replaced pkg_resources with importlib

Removed

• Python 3.8 support (EOL).

v2.1.0

Fixed

• Updated documentation with inference and sequence command renaming.
• Changed default model resolved from bam file from variant to consensus.
• Fixed issue with initializing inference in Medaka tandem model.
• Fixed a memory leak in the Medaka C library and removed redundant memory objects to reduce the footprint.

Changed

• Fully refactored and redesigned medaka tandem code and optimised CPU-based execution.
• Read-level models cannot be used with medaka tandem.
• get_trimmed_reads now also returns the phase-set, hap and read ids.

Added

• Consensus models for v5.2.0 basecaller models.
• Added support for read-level consensus models for v5.0.0 and v5.2.0 basecaller models.
• Models dna_r10.4.1_e8.2_5khz_400bps_sup and dna_r10.4.1_e8.2_5khz_400bps_hac added
  as aliases to those without _5kz_ in their names.
• Added -B option to medaka_consensus to allow passing a bed file or region to polish
  via medaka inference --regions.
• Added --cpu option to medaka inference to force CPU and avoid searching for GPUs.
• New output format for medaka tandem tailored for population studies.
• New fields to medaka tandem output: depth, read lengths, read names, phase sets, and MAD of read lengths.
• Read length–based outlier detection in medaka tandem.

v2.0.1

Fixed

• medaka smolecule was broken by change from medaka consensus to medaka inference.

Changed

• Improved error message when model is not found.

v2.0.0

Switched from tensorflow to pytorch.

Existing models for recent basecallers have been converted to the new format.
Pytorch format models contain a _pt suffix in the filename.

Changed

• Inference is now performed using PyTorch instead of TensorFlow.
• The medaka consensus command has been renamed to medaka inference to reflect
  its function in running an arbitrary model and avoid confusion with medaka_consensus.
• The medaka stitch command has been renamed to medaka sequence to reflect its
  function in creating a consensus sequence.
• The medaka variant command has been renamed to medaka vcf to reflect its function
  in consolidating variants and avoid confusion with medaka_variant.
• Order of arguments to medaka vcf has been changed to be more consistent
  with medaka sequence.
• The helper script medaka_haploid_variant has been renamed medaka_variant to
  save typing.
• Make --ignore_read_groups option available to more medaka subcommands including inference.

Removed

• The medaka snp command has been removed. This was long defunct as diploid SNP calling
  had been deprecated, and medaka variant is used to create VCFs for current models.
• Loading models in hdf format has been deprecated.
• Deleted minimap2 and racon wrappers in medaka/wrapper.py.

Added

• Release conda packages for Linux (x86 and aarch64) and macOS (arm64).
• Option --lr_schedule allows using cosine learning rate schedule in training.
• Option --max_valid_samples to set number of samples in a training validation batch.

Fixed

• Training models with DiploidLabelScheme uses categorical cross-entropy loss
  instead of binary cross-entropy.

v1.12.1

(Probably) final version of medaka using tensorflow. Future versions will use
pytorch instead.

Fixed

• medaka_consensus: only keep bam tags if input file matches joint polishing pipeline.
• Pin numpy to <2.0.0.

Added

• Consensus and variant models lookup for v3.5.1 Dorado models.

v1.12.0

Fixed

• tandem: Use haplotag 0 in unphased mode.
• tandem: Don't run consensus if regions set is empty.

Added

• Models for version 5 basecaller models.
• Expose sym_indels option for training.
• Expose --min_mapq minimum mapping quality alignment fitering option for medaka consensus.
• tandem: Option --ignore_read_groups to ignore read groups present in input file.
• Wrapper script medaka_consensus_joint and convenience tools (prepare_tagged_bam,
  get_model_dtypes) to facilitate joint polishing with multiple datatypes.

v1.11.3

Added

• Consensus and variant models for v4.3.0 dorado models.

v1.11.2

Added

• Parsing model information from fastq headers output by Guppy and MinKNOW.

Changed

• Additional explanatory information in VCF INFO fields concerning depth calculations.