Skip to content

Releases: YeoLab/flotilla

v0.3.2

08 Aug 18:44
Compare
Choose a tag to compare
v0.3.2 Pre-release
Pre-release

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

v0.2.6 (April 10th, 2015)

10 Apr 22:41
Compare
Choose a tag to compare

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

v0.2.5 (March 3rd, 2015)

04 Mar 22:21
Compare
Choose a tag to compare

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

v0.2.4 (November 23rd, 2014)

23 Nov 15:46
Compare
Choose a tag to compare
Pre-release

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__

v0.2.3 (November 17th, 2014)

18 Nov 17:52
Compare
Choose a tag to compare
Pre-release

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"

Docs deployment, fix version info

08 Nov 00:06
Compare
Choose a tag to compare
Pre-release

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

Documentation updates

New features and new datapackage spec

06 Nov 13:05
Compare
Choose a tag to compare
Pre-release
0.2.0

changed outlier detection to operate on only 2 PCs

0.1.1

13 Oct 18:25
Compare
Choose a tag to compare
0.1.1 Pre-release
Pre-release

re-release to trigger DOI