v0.2.6 (April 10th, 2015)

This is a patch release, with non-breaking changes from 0.2.5.

New features

• Add a :py:class:.data_model.SupplementalData data type, which allows the
  user to store any pandas.DataFrame on the :py:class:.data_model.Study
  object as study.supplemental. This is essentially user-driven caching.

Plotting functions

• Changed default loadings plot of PCA to a heatmap of the first 5 PCs

Bug fixes

• Fixed :py:func:.data_model.Study.save() to actually save:
  • Gene Ontology Data
  • Minimum number of mapped reads per sample
  • Minimum number of samples to use per feature, at the specified threshold
    (e.g. use features with TPM > 1 in at least 20 cells)
• Fixed :py:func:.data_model.base.subsets_from_metadata to use boolean
  columns properly, which allows for boolean columns in
  :py:class:.data_model.MetaData and
  :py:attr:.data_model.BaseData.feature_data

Miscellaneous

• Streamlined test suite to test fewer things at a time, which shortened the
  test suite from ~20 minutes to ~3 minutes, about 85% time savings.
• Improved accuracy (fewer false positives) in splicing modality estimation
• Added requirement for new non-plotting features to at least be documented as
  IPython notebooks, so the knowledge is shared.
• Changed PCA plot to place legend in "best" place
• Changed default plotting marker from a circle to a randomly chosen symbol
  from a list
• Violinplots are now variable width and expand with the number of samples
  • This was changed in :py:meth:.data_model.Study.plot_gene,
    :py:meth:.data_model.Study.plot_event and
    :py:meth:.data_model.Study.plot_pca when plot_violins=True
• Add info about data type when reporting that a feature was not found
• Fix lack of tutorial on how to create a datapackage