- Version 0.19.0
- Version 0.18.0
- Version 0.17.1
- Version 0.17
- Version 0.16.4
- Version 0.16.3
- Version 0.16.2
- Version 0.16.1
- Version 0.16 (Nov 2016)
- Version 0.15 (Nov 2016)
- Version 0.14 (20th June 2016)
- Version 0.13 (27th May 2016)
- Version 0.12 (9th May 2016)
- Version 0.11 (April-May 2016)
- Version 0.10
- Version 0.9
- Version 0.3
- Version 0.2
- Version 0.1
- Update GDSCTools to use latest Pandas version (0.20); in particular the .ix getter is deprecated and should be replaced by loc/ilc
- pin version of pandas to 0.20 and colormap to 1.0.1 in the setup
- FDR not taken into account in the volcano as shown in https://github.com/CancerRxGene/gdsctools/issues/168
- move from nosetests to pytest and fix tests accordingly
- Fix gdsc1000 module with new methods and documentation
- add test for module gdsc1000, which has been refactored and cleanup
- Fix GDSC links to fetch drug/genomic feature data sets
- Fix bug in regression.rules pipeline (create missing directory)
|summary:||Fixing bunch of deprecated warnings, working regression pipeline based on snakemake|
CHANGES and BUG Fixes:
- regression (snakemake pipeline)
- add missing init and regression modules
- starting to use colorlog
- add regression script to create the snakefile workflow easily
- a snakemake pipeline for the regression analysis
- Report for the regression analysis
- Fix regression dendogram plot
- Fix bug leading to NA in effect size reported by Carlos P. (private communication)”
- Omnibem: drops the NA instead of replacing by “”
- Fix pending issue related to #153 ic_input.csv”, “test_gf_input.csv” for the case where some media factor are missing. This is now handle properly.
- Fix #151 : large integer are not cast properly with consequence that indices are strings, not integers leading to further issues in the HTML pages.
- anova_one_drug_one_feature_custom allows to perform any regression using formula like in R. This is not for production but should be useful to perform custom analysis
- Include the MEDIA factor boxplot in the library and reports
Fix issue #156 (GDSC failures in some cases). This was due to special MOBEM input files for which no tests are performed. In such cases, some codes were failing in ANOVAReport and ANOVAResults, which have been fixed in this release.
Fix buggy volcano plot (no plot if no data); if FDR threshold below minimum value, set fdr_threshold to minimum value so that it scaled the plots properly. Now, users can add as many lines as desired using settings.additional_fdr. pvalues found to be NAN are set to 0 to prevent plotting issues.
- anova module: regression in the case Y ~ C(TISSUE) + C(MSI) + feature,
the tissue sum of squares was using N-1 tissues (one missing).
- anova module: regression in the case Y ~ C(TISSUE) + C(MEDIA) + C(MSI) + feature,
the media sum of squares was not normalised properly.
- elastic_net module renamed into regression
- ANOVASetting prints keys in alphabetical order (instead of randomly)
- ANOVASetting: regression_formula is added; other regression_XX settings are not removed but not used anymore.
- GenomicFeature reader: if a tissue is empty, it is replaced by UNDEFINED.
- standalone: the drug option must be an integer. THis is now caught are the option level, not later in the code.
- anova module: remove code related to elastic net, ridge, and lasso. This won’t be used in production with ANOVA. EN, Ridge and Lasso are used in the regression module and will be part of an independent type of analysis. See NEWS
- Add Ridge + Lasso + LassoLars classes in addition to ElasticNet regression method into the regression module.
- Add more features in regression module (boxplot, dendogram)
- New regression notebook in the notebooks directory
- anova module: We can now use any combo of regression formula using statsmodels. This is slower but one can do use any formula accepted by statsmodels. The previous faster code is still used for the standard analysis.
- ElasticNet: new method elastic_all()
- plot_elastic_weight in the gallery
- ElasticNet plot_weights is now split into plot_weights and plot_importance.
- Fixes missing files in the pypi distributino (MANIFEST changed)
DrugDecode: In brief, the DRUG ID in the IC50 input file and the DrugDecode files should be integers. Some old data sets use the following convention to refer to a drug Drug_<ID>_IC50 and so DrugDecode was using the same convention. However, we now convert this type of identifier into integers. This is done internally for the IC50 file, however, was not done inside the DrugDecoder file. This is now effective.
- HTML reports when using the GDSC class:
- Company names now appear systematically in the top of the company data packages.
- Drug Names were missing and do now appear in top of the relevant HTML pages.
Boxplots: If a DrugDecode file is provided Boxplots show the DRUG ID and the real drug name in the matplotlib and JS boxplots
- Reader class simplification and improvments: files can now be compressed using gzip but also xz, zip and bz2 formats. The NA can be encoded as NA or NaN strings. Spaces are interpreted as NA.
- Sort DrugDecode’s dataframe columns
- Updated all documentation
- Fix scaling of the data with newest version of scikit-learn
- fix typo in the setup.py file. Passed travis + all tests before main release.
- add missing CSS in the distribution
- tissue specific analysis computational time decreased by 50% by dropping the creation of dataframe and using a simple numpy array inside ANOVA.anova_one_drug_one_feature
- Similarly, boxplots for tissue, MSI and all associations are now created using JS.
Data packages have been refactored. The major difference concerns the HTML layout (most HTML files are now in the sub-directory called associations) so that is it cleaner at the top level. The volcano plots are not in PNG format anymore but pure HTML/JS, which can be exported manually. The consequences is that the creation of data packages is 10 times faster.
The standalone application had 2 options removed: –feature (alone) and –fast options
Drug Identifier are now handled as pure integer. For back compatibility, old files that mix up IC50 and Genomic Features (e.g. v17 data) are still interpreted; the DRUG ID in that case are written as Drug_ID_IC50 and are transformed as just <ID> everywhere.
associations output were named 1.html, 2.html... and are now named a1.html, a2.html...
Because DRUG_ID are now integer and all HTML stored in the same directory the naming of the HTML files have been altered (e.g., associations starts
Report now accepts only one argument (the anova isntance). Second argument (results) is now optional. If not provided, ANOVA are computed on the fly
Multicore module removed but ANOVA.anova_all has multicore option. This seems to work on Linux systems. Not tested on windows or MacOsX
IC50 may have duplicated drug ids (at different concentrations). Not good practice but that the format of e.g. v18, v19 IC50 files. A class IC50Cluster was created to interepret those files. ANOVA will switch to IC50Cluster automatically if there are duplicated files.
Settings: low_memory option has been removed
- The parameter pvalue_threshold in the general settings was changed from infinite to 10e-3. This has an effect on the numlber of significant hits reported in the HTML reports and volvano plots. This should not have a strong impact on the number of hits but guarantees a reasonably low pvalue before multiple testing
- If an input file named with .csv extension but the content is tabulated, there was no immediate error but lead to errors later (e.g. in ANOVA), which is difficult to debug. Now, in such cases, an error will occur immediately when reading the file.
- The warnings about MEDIA factor is removed since most of the files do not contain that column.
- The data packages were stored in the “ALL” directory, which may be a TCGA tissue by itself. This has been renamed into “tissue_packages”.
- add missing file in the setup.py
- Fixes the missing data package in the setup for pip installation
- Elastic notebook and module implemented
- GenomicFeatures has now a compression method
- anova module was split into modules + anova so that elastic_net module can inherit from module
- all share/data moved to gdsctools data
- add scikit-learn dependencies
- Fix onevent picking in the volcano plot and use 4 digit for the FDR plot
- Fixes issue #127 (If MSI factor missing, the anova still tries to use it)
- Fixes issue #126 (–out-directory ignored in gdsctools-anova pipeline)
- Fixes issue #125 and #124 (HTML report links broken)
- Fix set_cancer_type to accept lists of tissues again
- Fixes #119 by adding more tests.
- reactivate get_significant hits functions.
- rename ANOVAResults.get_significant_hits into get_html_table
Lots of changes in this version but for users the API should be very similar.
- Add a new factor called MEDIA_FACTOR. If not provided, genomic feature matrix can populated the MEDIA_FACTOR column automatically.
- add a class COSMICInfo and a related data file called cosmic_info.csv.gz to get information about COSMIC ids. Replaces COSMIC class, which was removed.
- add new class GDSC to perform the entire analysis splitting data across companies found in DrugDecode and across cancer types.
COSMIC class removed and replaced by COSMICInfo class
- Column name convention:
- FEATURE_ANOVA_pval –> ANOVA_FEATURE_pval
- MSI_ANOVA_pval –> ANOVA_MSI_pval
- TISSUE_ANOVA_pval –> ANOVA_TISSUE_pval
- FEATURE_ANOVA_FDR_% –> ANOVA_FEATURE_FDR
- new column named ANOVA_MEDIA_pval
- to be constistent, names such as FEATURE_pos have now underscores to separate words e.g., (FEATUREpos –> FEATURE_pos, FEATUREneg –> FEATURE_neg, deltaMEAN –> delta_MEAN).
gdsctools.volcanomodule to use new naming convention.
SAMPLE_NAME is not required anymore in the genomic features. This is indeed just an annotation and is now encoded in the flat file cosmic_info.csv.gz (see above)
anova, anova_results modules:
- Implement new factor (MEDIA) in the regression
- Uses new naming convention for the columns as described above
- When initialising a ANOVA instance, prints the factor that will be included.
- add new option (set_media_factor) to populate the MEDIA column automatically
- ‘Sample Name’ or SAMPLE_NAME are deprecated. There are removed from the genomic_feature matrix if found.
Uses MEDIA_FACTOR column in addition to MSI and tissue columns
shift attribute is now read-only and set automatically
add a function to fill media column automatically
print function is more verbose
volcano: uses new naming convention for the columns as described above.
readers: improved DrugDecoder and renamed into DrugDecode (issue #102 and #101)
add new settings and code to apply pvalue correction at drug level rather than global level.
add new module to find chemblId/ChemSpider from drug name.
- add settings as json file in the HTML report
- ANOVAResults has now a volcano() method
- add read_settings method in ANOVA
- add code in the HTML tree directory to reproduce HTML report and results
anova_one_drug now returns an ANOVAResults object
Restructure data package tree directory (#83)
- Default header have changed:
- COSMIC ID –> COSMID_ID
- Sample Name –> SAMPLE_NAME
- MS-instability Factor Value –> MSI_FACTOR
- Tissue Factor Value –> TISSUE_FACTOR
Previous values will still be accepted but deprecation warning added.
- Fixes #89 (tight layout buggy under MAC)
- MSI/Sample/Tissue columns in the genomic features are not required anymore.
- FDR lines in volcano plots are now using interpolation and therefore more precisily placed. Fixes #57
- volcano plot improvments. Fixes #79, #80, #81
- Fixes issue #72 to get the drug_decoder information from the ANOVA class.
- Fixes issue #76 to drop IC50 cosmic Id not found in the genomic feature matrix
- Readers (e.g. IC50) can now read CSV files with commented lines (# character) issue #78
- Readers can now ignored columns that are not named (usually first column of index exported by excel document)
- IC reader figure out automatically if the prefix “Drug” has been used. It so, it drops other irrelevant columns. Useful if genomic features and IC50 are mixed together.
- IC50 and GenomicFeatures, DrugDecode now accepts both TSV and CSV format (gziped or not)
- add more datasets for testing purposes
- double checked results on BLCA tissue v17 and v18
- Finalise a first version of the standalone application
- ReadTheDocs documentation is now on line gdsctools.readthedocs.org
- GDSCTools has now all features of the original R version
- With in addition: - a standalone application - test suite - documentation
- benchmarking for the analysis in about 20 minutes 265 drugs and 680 features across 980 cell lines. HTML report takes as much time.