v0.3.1 (August 8th, 2016)

This is a patch release, with non-breaking changes from v0.3.1.

Plotting

• Removed filling NA of :py:func:.visualize.gene_ontology.plot_go_enrichment with arbitrary values

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

This is a patch release, with non-breaking changes from v0.2.4. This includes
many changes and bugfixes. Upgrading to this version is highly recommended.

New features

• Added data structure and functions for calculating gene ontology enrichment in flotilla.data_model.Study.go_enrichment, using the data structure flotilla.gene_ontology.GeneOntologyData

Plotting functions

• New function flotilla.data_model.Study.plot_expression_vs_inconsistent_splicing() shows the percent of splicing events in single cells that are inconsistent with the pooled samples. Has the option to choose an expression cutoff.
• Add options to flotilla.data_model.Study.plot_pca and flotilla.data_model.Study.interactive_pca:
  • Keyword argument color_samples_by will take a column name from the
    metadata DataFrame, to color samples by different columns in the
    metadata.
  • Keyword argument scale_by_variance is a boolean which when True
    (default) will scale the x and y axes by the explained
    variance of their individual principal components (PC1 for x and
    PC2 for y). If False, then the axes are the same scale, by the
    variance in PC1. Often this will "squish" down the samples in the y-axis.

API changes

• flotilla.data_model.Study.plot_classifier returns a flotilla.visualize.predict.ClassifierViz object
• Multi-index columns for data matrices are no longer supported
• Modalities are now calculated using Bayesian methods
• flotilla.data_model.Splicing._subset_and_standardize now doesn't fill
  NAs with the mean Percent spliced-in/Psi/\Psi score for the
  event, but rather replaces NA with the value 0.5. Then, all values for
  that event are transformed with arc cosine
  so that all values range from -\pi to +\pi and are centered
  around 0.

Bug fixes

• Fixed issue with flotilla.data_model.Study.tidy_splicing_with_expression and
  flotilla.data_model.Study.filter_splicing_on_expression which
  had an issue with when the index names are not "miso_id" or
  "sample_id".
• Don't cache flotilla.data_model.BaseData.feature_renamer_series, so you
  can change the column used to rename features

Miscellaneous

• Add link to PyData NYC talk
• Add scrambled dataset with ~300 samples and both expression and splicing
• Fix build status badge in README
• Removed auto-call to %matplotlib inline call within
  flotilla.visualize because it messes up the make lint call
  and it's dishonest to the user to be messing with their IPython under the
  hood. It's possible they don't want the plotting to be inline, but rather
  in a separate X-window as specified by their $DISPLAY environment
  variable.
• Reformatted all code to pass make lint and make pep8, and these
  standards will be enforced for all future enhancements.
• Add Gitter chat room badge to README

This is a patch release, with non-breaking changes from v0.2.3.

Plotting functions

• New clustered heatmap and Study.plot_clustermap and Study.plot_correlations (!!)

API changes

• Study.save() now saves relative instead of paths, which makes for more portable datapackages
• Underlying code for DecompositionViz and ClassifierViz now plots via plot() instead of __call__

This is a patch release, with non-breaking changes from v0.2.2.

Compute functions

• Restore Study.detect_outliers Study.interactive_choose_outliers and Study.interactive_reset_outliers

Plotting functions

• Add Study-level NMF space transitions/positions

Bug Fixes

• embark wouldn't work if metadata didn't have a pooled column,
  now it does
• BaseData.drop_outliers would actually drop samples from the data,
  but we never want to remove data, only mark it as something to be removed so
  all the original data is there
• For all compute submodules, add a check to make sure the input
  data is truly a probability distribution (non-negative, sums to 1)
• BaseData.plot_feature now plots all features with the same name
  (e.g. all splicing events within that gene) onto a single fig object

Documentation

• Restore some lost documentation on :py:class:.BaseData and
  :py:class:.Study

Other

• Rename modalities that couldn't be assigned when bootstrapped=True in
  compute.splicing.Modalities, from "unassigned" to "ambiguous"

This is a patch release, with non-breaking changes from v0.2.0.

Documentation updates

• Update documentation (http://yeolab.github.io/docs is release, docs-dev is master)
• Fixed issue with pip install reported by
  @roryk

re-release to trigger DOI