HATCHet v2.0.1

HATCHet 2 ready for bioconda upload

What's Changed

• bug fixes and additional QC by @balabanmetin in #194
• Update init.py by @simozacca in #201
• Update pyproject.toml by @simozacca in #202
• Update pyproject.toml by @simozacca in #203

New Contributors

• @balabanmetin made their first contribution in #194

Full Changelog: v1.2.0...v2.0.1

HATCHet2 (v2.0)

This release includes all of the features described in the HATCHet2 preprint posted July 13, 2023, including mirrored haplotype BAF (mhBAF) inference, as well as variable-width binning and locality-aware clustering that were integrated in version 1.0.0.

HATCHet v1.1.1

This version of HATCHet fixes a bug introduced in v1.0.2, and adds a feature allowing the end-end HATCHet demo to run.

• Fixed a bug in the count_alleles step that would have thrown a IndexError: list index out of range exception in certain cases.
• Fixed a bug in multiprocessing (that would have shown up in the count_alleles step) that would have caused the number of chromosoms written to .1bed files to match the number of worker threads, ignoring the rest. Thank you @mlewinsohn and @alvinwt for uncovering this bug.
• Added an optional chromosomes key in the [run] section of hatchet.ini to allow HATCHet demo to run.

HATCHet v1.0.3

This version of HATCHet fixes a bug with error reporting, wherein certain exceptions raised at runtime by HATCHet would have a missing message string. This would only affect situations where processing would normally have failed, and an exception raised by the code.

Users with failing HATCHet pipelines should now have a better diagnostic message to work with.

HATCHet v1.0.2

This version of HATCHet fixes a bug with the hatchet run command, specifically when running the phase-snps step. The order of arguments passed on to phase-snps was incorrect. This would have shown up as an immediate error in hatchet run. This has now been fixed.

The count-alleles step has been slightly tweaked so that any underlying runtime errors in the step are propagated as exceptions to the caller, instead of (in many cases) the step seeming to take forever. This is expected to help in debugging previously-stalled scenarios when running this step.

HATCHet v1.0.1

HATCHet 1.0.1

The 1.0.1 release of HATCHet has a number of algorithmic improvements over the 0.x versions:

A variable length binning approach to ensure that each bin contains some minimum number of SNP-covering reads.
Reference-based phasing and quasi- maximum likelihood EM approach to capture allelic imbalance.
Locality-based clustering using a Hidden Markov Model.

These improvements are all turned on by default. To emulate pre-1.0 behavior, you will want to:

Use HATCHet's count-reads-fw command instead of count-reads (fw stands for fixed width).
Use HATCHet's combine-counts-fw command instead of combine-counts.
Use HATCHet's cluster-bins-gmm command instead of cluster-bins.

HATCHet v0.4.14

This release of HATCHet adds a check command that will check your environment for runtime dependencies that HATCHet relies on (like a useful LP solver like Gurobi). Currently this command behavior is identical to the check-solver command. The check-solver command is still supported for now, but users are encouraged to use the check command instead. This will allow us to add more comprehensive runtime checks in the future.

HATCHet v0.4.12

Fixed a bug in the count_alleles step which would have caused failure to generate temporary files, if an output directory is explicitly specified.

HATCHet v0.4.10

This release of HATCHet fixes a bug where multiple parallel runs of the count_alleles step for the same chromosome (e.g. for multiple patients) would have created temporary files that would clash with each other. This temporary file creation step is now protected by using facilities from the tempfile module.

HATCHet v0.4.9

This HATCHet release fixes a bug:

• End users who built HATCHet from source using the environment variable HATCHET_BUILD_NOEXT set to 1 (i.e. not building the fast C++ solver extension of HATCHet that requires Gurobi to be pre-installed, but instead relying on pyomo-supported solvers that HATCHet also supports), would previously have failed to use the compute_cn step of HATCHet. This is fixed now.

There are two enhancements:

• The compute_cn step, when using pyomo solvers, will now output the number of variables and constraints, helpful to determine the size of the problem that this factorization step is trying to solve.
• Faster and more atomic unit tests to aid development efforts.