One Codex

Changelog

Follow up on the latest improvements and updates.

RSS

new

improved

fixed

Client Library

onecodex library v1.0.0

This release contains breaking changes to plotting and classification results functions such as how
SampleCollection
is instantiated and how
metric
,
diversity_metric
, and
rank
are passed to
SampleCollection.to_df
and plotting functions.
Previously,
metric
and
normalize
were determined when a
SampleCollection
was instantiated. Now, those parameters are passed to
.to_df
and plotting functions separately, allowing users to change metrics at plot time.
Example:
##
# in 0.19.x
collection = onecodex.models.SampleCollection(samples, metric='readcount_w_children', normalize=True)
# produce a dataframe using readcount_w_children as the metric
collection.to_df()
# to plot a different metric, create a new SampleCollection
collection = onecodex.models.SampleCollection(samples, metric='abundance_w_children')
collection.plot_bargraph()
##
# in 1.0.0
collection = onecodex.models.SampleCollection(samples)
collection.to_df(metric='normalized_readcount_w_children')
# switch metrics without re-instantiating
collection.plot_bargraph(metric='abundance_w_children')
# for backwards compatibility, the following still works but prints a warning
collection = onecodex.models.SampleCollection(samples, metric='readcount_w_children')
# defaults to the metric provided when the collection was created
collection.to_df()
Added
  • metric
    is now an argument for all plot and stats functions. By default, it is
    auto
    , which is determined by
    SampleCollection.automatic_metric
    based on existing logic
  • SampleCollection.__repr__
    has been updated to differentiate it from lists:
    <SampleCollection[Samples] length=60 : [<Samples 0b2d0b5397324841: "SRR4408293.fastq">, ...
  • Added type annotations to
    onecodex.Api()
    so that models are now known to static analyzers (e.g.,
    ocx.Samples
    )
  • SampleCollection.automatic_rank
    now returns the best default
    onecodex.enums.Rank
    to use based on the contained results
  • SampleCollection.automatic_metric
    now returns the best
    onecodex.enums.Metric
    value to use based on the contained results
Changed
  • You can change plotting metrics without re-instantiating the
    SampleCollection
  • In alpha- and beta-diversity related functions (e.g.,
    plot_mds
    ), the argument metric was changed to either
    diversity_metric
    or
    distance_metric
    . The
    metric
    argument in those functions now corresponds to the abundance metric (see
    onecodex.enums.Metric
    )
  • onecodex.notebooks.report
    functions no longer raise a
    OneCodexException
    if used outside of IPython.
Removed
  • ClassificationDataframe.ocx
    has been removed
  • SampleCollection()
    no longer takes
    metric
    or
    normalize
    arguments. Those have been merged into a single
    metric=
    argument that takes a string or
    onecodex.enums.Metric
    enum value, which is now passed into dataframe and plotting functions directly
  • normalize
    has been removed. Normalized metrics are now available as individual
    Metric
    enum values
  • Removed
    test-python3-w-simple-json
    from CI. It randomly started breaking. We don't think we need it anymore since we've moved away from Potion
Fixed
  • readcount
    being used instead of the intended metric when clustering samples for PCA/Heatmap when plotting from a
    SampleCollection
  • Plot title and table export column names have been updated to be more specific and match custom plots

improved

API

Improved speed on sample searches

Improved
  • We've sped up sample search, particularly when searches include filtering by
    updated_at
    .

improved

Client Library

onecodex library v0.19.5

Changed
  • onecodex
    library v0.19.5:
    ocx.Samples
    and
    ocx.Metadata
    now use a more performant, cursor-based pagination method

fixed

Sequencing dashboard moved; arguments display for workflows; ATCC standards metadata

Changed
  • We renamed the Sequencing "Order Dashboard" to "Dashboard" and moved it to the top of the Sequencing sub-menu on the navigation bar.
Fixed
  • We fixed a display issue for hiding or showing optional Arguments on the confirmation page to run workflows.
  • We fixed an error that was preventing recording of metadata from the metadata form displayed when launching ATCC Standards analyses.

new

fixed

Cursor-based pagination; various sequencing information fixes

New
  • We introduced opt-in cursor-based pagination to many API endpoints, to improve pagination across large numbers of samples or analyses for instance.
Fixed
  • We fixed an issue where filtering the Sequencing Order Dashboard by certain sequencing states did not correctly filter those states.
  • We fixed an issue whereby attempting to register sequencing samples where the sample has been retested resulted in an error.

improved

Notebook list loading speed

Improved
  • We've improved loading the list of notebooks on a user's Notebooks page.

improved

Sequencing Order Dashboard filtering improvements

Improved
  • We've improved status filtering selections on the Sequencing Order Dashboard.

fixed

KO annotations deprecated from Custom Plots

Deprecated
  • We deprecated KEGG Orthology (KO) annotations from functional Custom Plots.

improved

Workflow sub-task caps

Improved
  • We added a cap to the amount of CPUs and memory a sub-task can request to prevent over-consumption of resources.

new

improved

fixed

Client Library

Custom plots beta diversity; onecodex library v0.19.4

Fixed
  • We fixed an issue whereby beta diversity distances in Custom Plots were returning incorrect values. This was due to scikit-bio coercing the underlying counts matrix into 32-bit ints instead of 64-bit.
Improved
  • We updated the version of our underlying framework for the One Codex web application.
New
  • onecodex client library v0.19.4 released
  • Adds onecodex interleave command for generating interleaved fastq files from a pair of R1+R2 files
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