========== Changelog ========== 0.10.6 ------------------------- This release is adding key features to the OTTER class and command - OTTER GPU - OTTER on command line - OTTER LIONESS class - OTTER LIONESS command line We'll need to reconcile the the OTTER and PANDA reading functions to be consistent, but for the moment we are keeping them separate. 0.10.5 ------------------------- - Fixed BONOBO pvalue computation 0.10.4 ------------------------- - Adding PUMA to the readme and documentation - Folder renamed from ligress to bonobo 0.10.3 ------------------------- - Fixed LIONESS CLI that was broken after removing the save_memory flag - Added exception for case where the motif genes do not match the expression genes 0.10.2 ------------------------- - Fixed readthedocs - Removed save_memory from LIONESS (CLI). The first PANDA needs to keep the PANDA value in memory - Added BONOBO to CLI 0.10.1 ------------------------- - Added BONOBO to docs. - Added LIONESS examples to docs. - Fixed mistake in README. 0.10.0 ------------------------- - Added BONOBO to the zoo! - Cobra has been updated and integrated with PANDA. 0.9.16 ------------------------- - Added COBRA to the zoo! - We no longer costrain the igraph version to be older than 0.10. This will probably change the community assignment results, but the upgrade has been recommended by the igraph developers. 0.9.13 ------------------------- - We have added some options to LIONESS: single lioness files can be saved in HDF (fmt='h5') which saves a lot of time and memory. By passing ignore_final to lioness (with save_single_lioness) each lioness is discarded after being saved, hence you won't have all lioness networks in memory at the same time. - PANDA can be run with_header from CLI - Added pytables/tables in dependencies. 0.9.12 ------------------------- - We are changing the PANDA outputs and default flags. For now we are updating the command line call only, behavior is kept as in 0.9.11 for the internal functions. By passing `old_compatible = False` the final output will always have column headers and indices. - PUMA and PANDA do not save_tmp as default. - lioness for puma has been fixed - Fixed PANDA data preprocessing bug 0.9.11 (2022-11-04) ------------------------- - Added LIONESS for DRAGON with tests - PANDA preprocessing expression: In Panda preprocessing there was a problem with indices. Using gene2idx.get(x, 0) always give you the index 0 if x is missing fro m gene2idx.get (like a gene in gene expression and not in motif, since gene2idx is build on top of the intersection of expression and motif). Now we use gene_names to both create the indices for self.expression and to access with .loc[] the expression data frame self.expression_data - New PANDA tests - Updated LIONESS start and end parameters so that they are independent of the background. Example: One can now run panda on 100 samples and then apply LIONESS on only the first 10. - Added LIONESS subset parameter: passing subset parameters (a list of indices or sample names, [1,2,10]) allows to run LIONESS only on specific samples. This parameter has priority over the start and end parameters. 0.9.10 (2022-10-28) ------------------ - Fixing single/double precision for GPU - Clearing GPU after computation to free more memory 0.9.9 (2022-10-21) ------------------ - added the case for square nonsymmetric matrices for normalization in panda - Updated tests for panda and lioness to match MATLAB - Fixed Panda-Lioness GPU inconsistencies - Forcing igraph<0.10, otherwise community assignment results change. This will need further investigation for the future. - Fixed lioness GPU export (now lioness allows to save the full matrix, with explicit edge and sample names). 0.9.6 (2022-06-10) ------------------ - Ligress filters PPI according to input motif 0.9.5 (2022-05-24) ------------------ - Added output with sample names in Lioness - ligress sample names are setup as strings - correct order of motif prior in ligress 0.9.4 (2022-05-20) ------------------ - First ligress release - solved puma bug 0.9.2 (2022-03-04) ------------------ - added command line interface (panda, lioness) - updating documentation 0.9.0 (2022-02-11) ------------------ - we fixed the panda-lioness and puma-lioness behavior ( panda was passing the updated motif to lioness ). The results are now compatible with the ones of netzooR. - removed py3.6 support - updated version on anaconda.org 0.8.0 (2021-06-08) ------------------- - support for Python v3.9 - addition of DRAGON + unit tests +tutorial and many bug fixes that Daniel and Marouen have been doing as a user requests 0.7.2 (2020-07-18) ------------------ - PANDA reads arguments as dataframes in addition to file paths - changed condor ground truth to match output of `python-igraph 0.8.2 `_. 0.7.1 (2020-06-27) ------------------ - Major fix for OTTER behavior across platforms. 0.7.0 (2020-01-18) ------------------ - new tool: OTTER - unit test for OTTER - fix for PANDA `force` field - tweaks for compatibility of gpuPANDA with cupy 0.6.2 (Stockholm) (2020-05-15) ------------------------------ - Added gpuPANDA, which is a gpu-accelerated implementation of PANDA - Added gpuLIONESS - Added a gpuPANDA and gpuLIONESS tutorial - Fixed condor dependency to python-igraph (still under investigation in #82 ) 0.6.1 (2020-01-18) ------------------ - sambar tutorial - condor tutorial - added 3.8 to Ubunutu test server (along with 3.6 and 3.7 ) - Created three options for data processing in PANDA. - Union: adds rows for genes/TFs that are missing in at least one prior (expression, ppi, motif) - Intersection: removes TF/genes that missing in at least one prior - Legacy: previous data processing behavior - The default was set to union in netZooM, netZooR, netZooPy as it is the default in netZooC. 0.5.0 (2019-11-22) ------------------ - pysambar 0.4.0 (2019-11-18) ------------------ - pycondor 0.3.0 (2019-11-14) ------------------ - pypuma 0.2.0 (2019-11-13) ------------------ - pylioness 0.1.1 (2019-9-3) ------------------ - fixed call to save_memory=True 0.1.0 (2019-7-26) ------------------ - transition to python 3 - Changelog added to the doc - pypanda: original import and NaN values in normalized matrices are replaced with values normalized by the overall z-score. This allows running the Toy Data provided in this repository.