Change Log

Inferelator v0.6.3 August 15, 2023

New Functionality:

  • Accepts h5ad objects directly into the constructor

Bug Fixes:

  • Fixed several deprecated arguments in dependencies

Inferelator v0.6.2 May 8, 2023

New Functionality:

  • Generates & reports non-bootstrap model weights as part of results

  • Saves full model information into an h5ad file

  • Added new experimental prediction modules

  • Added new preprocessing & normalization options

Code Refactoring:

  • Logging messages now use logging module

Bug Fixes:

  • Fixed several errors when sparse data was passed unexpectedly

  • Corrected several deprecated numpy calls

  • Updated calls and version requirement to anndata

Inferelator v0.6.1 January 3, 2023

New Functionality:

  • Extended support for mRNA velocity & decay calculations

  • Added new experimental TFA modules

Code Refactoring:

  • Workflow, ResultProcessor, and InferelatorData restructured for readability and clearer commenting

Bug Fixes:

  • Slicing individual gene data returns numpy vector instead of anndata view

  • Corrected several deprecated pandas calls to eliminate FutureWarnings

Inferelator v0.6.0 September 14, 2022

New Functionality:

  • Support for grouping arbitrary genes from multiple tasks into learning groups

  • Workflow to learn homology groups together

  • Workflow to explicitly incorporate velocity and decay into learning

  • Added support for batching parallelization calls to reduce overhead when data is relatively small

Code Refactoring:

  • Refactored multi-task learning to parameterize tfs and genes for each task

  • Refactored parallelization around joblib & dask

  • Removed pathos and replaced with joblib

  • Optimized StARS-LASSO by replacing standalone LASSO with lasso_path

Bug Fixes:

  • Fixed several messages to be more informative

  • use_no_prior is appropriately applied in multitask learning

Inferelator v0.5.8 February 23, 2022

Bug Fixes:

  • Corrected combining multi-task gene and tf labels

Inferelator v0.5.7 September 29, 2021

New Functionality:

  • Added support for numba acceleration of AMuSR with .set_run_parameters(use_numba=True) (PR #46)

Code Refactoring:

  • Updated example scripts

  • Removed deprecated KVS multiprocessing and associated code

Bug Fixes:

  • Gene labels are included as the first column of the produced confidences TSV file by default

  • Matplotlib backend selection checks for non-interactive mode

Inferelator v0.5.6 August 16, 2021

New Functionality:

  • Added code to randomly generate noise in prior with .set_shuffle_parameters(add_prior_noise=None)

  • Added in-workflow benchmarks for CellOracle and pySCENIC

Code Refactoring:

  • Minor changes to matplotlib interface

  • Improved testing for multitask workflows

  • Improved error messaging around prior and gold standard

  • Switch from Travis.ci to GitHub Actions for continuous integration

Inferelator v0.5.5 April 29, 2021

New Functionality:

  • Added .set_regression_parameters(tol=None) to parameterize tolerances in AMuSR regression

Code Refactoring:

  • Profiled and optimized AMuSR code

Inferelator v0.5.4 April 23, 2021

Bug Fixes:

  • Fixed bug in multitask prior processing

  • Fixed bug in dask cluster setup

  • Suppressed stdout warning when output network MCC is not finite

Inferelator v0.5.3 March 22, 2021

New Functionality:

  • Added the ability to control threads-per-process when using dask

Bug Fixes:

  • Fixed bug in result dataframe that failed to create columns in older versions of pandas

Inferelator v0.5.2 January 29, 2021

New Functionality:

  • Added flag .set_shuffle_parameters(make_data_noise=True) to model on randomly generated noise

  • Output TSV files are gzipped by default

  • Added .set_output_file_names() as interface to change output file names

  • Added .set_regression_parameters(lambda_Bs=None, lambda_Ss=None, heuristic_Cs=None) for AMuSR regression

Bug Fixes:

  • Fixed bug(s) with dask cluster scaling

  • Fixed float precision bug in mutual information

Code Refactoring:

  • Added additional tests

  • Refactored AMuSR code

Inferelator v0.5.1 November 22, 2020

Bug Fixes:

  • Fixed bug that prevented PDF summary figure generation

Inferelator v0.5.0 November 14, 2020

New Functionality:

  • Changed output to include additional performance metrics (Matthews Correlation Coefficient and F1)

Bug Fixes:

  • Fixed several bugs around data loading

  • Fixed several float tolerance bugs

Code Refactoring:

  • Added additional tests

  • Improved dask cluster configurations

  • Improved documentation

Inferelator v0.4.1 August 4, 2020

New Functionality:

  • Added a regression module based on stability selection

  • Added a regression module that can apply any scikit-learn regression model

Bug Fixes:

  • Fixed row labels in matrix outputs

Code Refactoring:

  • Added additional tests

Inferelator v0.4.0 April 7, 2020

New Functionality:

  • Support for sparse data structures

  • Support for h5 and mtx input files

  • Added several flags that can change behavior of BBSR (clr_only, ols_only)

Bug Fixes:

  • Changed behavior of precision-recall to average the precision of ties instead of randomly ordering

Code Refactoring:

  • Refactored the core data structures from pandas to AnnData backed by numpy or scipy arrays

  • Data matrices are loaded and maintained as OBS x VAR throughout the workflow. Data files which are in GENE x SAMPLE orientation can be loaded if .set_file_properties(expression_matrix_columns_are_genes=False) is set.

  • Use sparse_dot_mkl with the intel Math Kernel Library to handle sparse (dot) dense multiplication

  • Improved memory usage

  • Added unit tests for dask-related functionality

  • Changed a number of error messages to improve clarity

Inferelator v0.3.2 December 19, 2019

New Functionality:

  • Improved error messages associated with misaligned data structures

  • Added example script and data for the multitask workflows

Bug Fixes:

  • Corrected several bugs when using the CrossValidationManager on multitask workflows

Code Refactoring:

  • This is the final release which will be fully py2.7 compatible

  • Additional unit testing

Inferelator v0.3.1 December 10, 2019

New Functionality:

  • Created a CrossValidationManager which handles parameter searches on workflows. Replaces the single_cell_cv_workflow which did not generalize well.

  • Workflow parameters are now set through functional setters like set_file_paths(), instead of through setting (cryptic) instance variables

  • Calculated transcription factor activities can be saved to a file prior to inference. This is set with workflow.set_tfa(tfa_output_file = “Filename.tsv”)

Bug Fixes:

  • Many

Code Refactoring:

  • Rebuilt the multitask workflow with TaskData objects instead managing data in many lists of things.

Inferelator v0.3.0 July 30, 2019

New Functionality:

  • Created a MultiprocessingManger for abstract control of multiprocessing.

  • Implemented a scheduler-worker model through the dask package for cluster computing.

  • Implemented a map model through the pathos implementation of multiprocessing for local computing.

  • Example scripts and datasets are now provided

Bug Fixes:

  • Many

Code Refactoring:

  • Rebuilt the core workflow

  • Workflow assembly by inheritance is managed with a factory function

  • Refactored regression to act as a mapped function for easier multiprocessing