QIIME 2 2020.6 is now available!

q2d2 · June 29, 2020, 3:46pm

The QIIME 2 2020.6 release is now available! Thanks to everyone involved for their hard work!

As a reminder, our next planned QIIME 2 release is scheduled for August 2020 (QIIME 2 2020.8), but please stay tuned for updates.

Check out the QIIME 2 2020.6 docs for details on installing the latest QIIME 2 release, as well as tutorials and other resources. Get in touch on the QIIME 2 Forum if you run into any issues!

Virtual machine builds will be available sometime within the next week - watch this topic thread for an update!

BREAKING CHANGES

q2-diversity
- core_metrics_phylogenetic: The n_jobs parameter has been renamed n_jobs_or_threads to accommodate a speedy new implementation of unifrac now being used
- core_metrics & core_metrics_phylogenetic: The phrase observed_features is replacing observed_otus, as "observed features" better describes the different ways in which users work with non-taxonomic features in QIIME 2 (an OTU is a feature, but a feature isn't necessarily an OTU)
- core_metrics & core_metrics_phylogenetic: n_jobs and n_jobs_or_threads no longer accept zero or negative integers as arguments. Users should pass auto to those parameters to use all available physical cores

Highlights of the release:

QIIME 2 Framework
- @thermokarst, @andrewsanchez, and @David-Rod worked up further developing the Usage API, which will allow plugin developers to showcase usage examples of their plugin actions, in an interface agnostic way!
  This included:
  - Enabling source tracking of initialized data
  - Adding a method to initialize data collections
- @thermokarst improved some of the developer documentation in the test harness.
- @Oddant1 increased level of validation of filenames to prevent creation of artifacts with incorrectly named data files.
docs
- @ChrisKeefe showed us how to peek at an Artifact in the Moving Pictures Tutorial
- @ChrisKeefe added a section to the Importing Tutorial for multiplexed fastq files with barcodes in sequences.
- @ChrisKeefe clarified the behaviors of qiime tools view and q2view
- @thermokarst added Native installation instructions for Windows users leveraging the Windows Subsystem for Linux
- @thermokarst added some rough guidelines for selecting an installation method that best fits your computational needs
- @thermokarst added examples of q2-demux's subsampling and sample filtering tools to the Atacama tutorial
- @Oddant1 Changed the wording of the suggestion to use the vega editor for the q2-longitudinal volatility plot to reflect the current implementation
- Several small typos were fixed, including one by @hmaru (GH)!
- @thermokarst overhauled the User Docs hosting infrastructure.
data-resources
- @Nicholas_Bokulich also added SILVA 138 release sequence and taxonomy files formatted for use with QIIME 2. Data were prepared and formatted using RESCRIPt (co-developed with @SoilRotifer)! See that tutorial for more details on how these files were generated, and a pipeline to reproduce this process!
- @Nicholas_Bokulich added new pre-trained classifiers for Greengenes 13_8 release and SILVA 138 release (the latest versions of both), trained using scikit-learn 0.23.1. These classifiers were built and tested in a new way, using RESCRIPt!
q2cli
- @thermokarst fixed up an error message: a tiny typo can cause a surprising amount of confusion!
- @andrewsanchez merged in the first iteration of the Usage API CLI driver . This should be considered as sort of "pre-release," for developers until the Usage API and usage examples are a bit more mature. Stay tuned for much more action in this realm in future releases!
QIIME 2 Studio
- @andrewsanchez fixed a bug that cropped up when trying to import data!
q2-feature-classifier
- @cherman2 (GH) helped remind us why we don't have multithreading options for the blast classifier - thanks for the research and code comments!
- @adamovanja (GH) added a trim-right option to the extract-reads action, allowing simulated reads to be trimmed at the 3' ends. This is useful for, e.g., emulating trimming options of reads coming from q2-dada2, to generate optimally trimmed reference sequences for classifier training as described here. Thank you adamovanja for fixing this issue, and @Sean_McKenzie for bringing it to our attention!
- @Nicholas_Bokulich improved the docs for extract-reads !
- @Nicholas_Bokulich trained new feature-classifiers using scikit-learn 0.23.1
q2-phylogeny
- @ebolyen added a new method, robinson-foulds, for comparing two phylogenetic trees!
q2-composition
- @thermokarst fixed a bug in ancom! The visualization had a propensity for (accidentally) attempting to divide by zero - never a good plan!
- @Oddant1 Removed the link to the vega editor on the ancom plot pending a rework of the plot for vega 5
q2-cutadapt
- @Oddant1 and @thermokarst added support for demultiplexing mixed-orientation single-indexed reads.
q2-feature-table
- @David-Rod added some usage examples to the merge method!
- @jwdebelius added a new method for re-naming features or samples in a table
- @thermokarst fixed a bug that caused summarize visualizations to sometimes display distorted column widths
- @Oddant1 Removed the link to the vega editor on the summarize plot pending a rework of the plot for vega 5
q2-alignment
- @gregcaporaso added a new action, mafft-add, which allows for the addition of unaligned sequences to an existing alignment
q2-quality-filter
- @thermokarst merged q-score and q-score-joined into the same method (q-score), and deprecated the q-score-joined method. This method will be removed in the fall 2020 release of QIIME 2.
q2-quality-control
- @Nicholas_Bokulich (aka Doc Bok) added a new filter_reads method that supports filtering SampleData[SequencesWithQuality] and SampleData[PairedEndSequencesWithQuality] artifacts (a.k.a. FASTQ sequence data) by alignment to a reference database. How might you use this? To filter human reads and other non-target (or junk) sequences prior to denoising or dereplication.
- @gwarmstrong transitioned alpha_phylogenetic and alpha_rarefaction to use Stacked Faith, a speed- and memory-optimized implementation previous available in alpha_phylogenetic_alt. alpha_phylogenetic_alt will be removed in the next release.
q2-diversity
- @patrickimran (GH) added a new jensenshannon beta diversity metric!
- @ChrisKeefe wired up q2-diversity-lib to perform alpha- and beta-diversity calculations for core-metrics and core-metrics-phylogenetic. See Breaking Changes above for related API changes.
- @Oddant1 fixed a bug allowing 0 variance numerical columns to slip past the filter in bioenv causing errors.
q2-diversity-lib
- @ChrisKeefe - this plugin calculates alpha- and beta-diversity measures, expands the number of available semantic types where appropriate, and provides measure-specific citation information.
q2-types
- @thermokarst added new transformers for working with per-sample-sequences in fun and interesting ways (dev alert!)
- @gregcaporaso added more aligned sequence transformers.
q2-vsearch
- @thermokarst fixed up a performance bug in the cluster-features-closed-reference method, resulting in potentially significant speedups for some use-cases.
- @angrybee (gh) added an awesome new visualizer fastq_stats for distilling single-end or paired-end sequences into FASTQ file statistics using vsearch!
- @Oddant1 added the ability for all vsearch methods to accept sequences shorter than 32nt
- @Oddant1 set --fasta_width 0 on invoked vsearch commands to prevent fasta records from being split across multiple lines
q2-longitudinal
- @Oddant1 removed the link to the vega editor from the volatility plot pending a rework of the plot for vega 5
q2-demux
- @Oddant1 and @thermokarst reworked summarize visualization to better inform the user of missing reads
q2-dada2
- @benjjneb added pseudo-pooling to all DADA2 workflows, allowing users to increase sensitivity to rare variants in samples, particularly singletons, as long as they were observed in other samples independently.
- @ebolyen squashed a bug where feature-tables containing only one feature were being mis-diagnosed as empty.
q2-sample-classifier
- @Nicholas_Bokulich gave the test suite some much needed TLC with a generous refactor.
q2-emperor
- @yoshiki and @antgonza updated to the latest release of Emperor 1.0.1 .
- @yoshiki fixed an issue where biplot arrows would incorrectly show while visualizing a parallel plot.
- @fedarko fixed an issue where continuous and divergent colormaps would be partially used in categorical data.
- @fedarko fixed a bug with sorting numeric and non-numeric values.
- @yoshiki fixed an issue where axes settings wouldn't load correctly from the Python API.
- @fedarko and @yoshiki updated various dependencies.
- Added the ability to select a group of samples and save the sample names to the users' clipboard. To do this, users need to hold shift and select the samples they are interested in:
  
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Happy QIIMEing!

Mechah · June 30, 2020, 8:35am

FYI: the link to the Naive Bayes classifier trained on Silva 138 99% OTUs full-length sequences gives a 404 error.
https://data.qiime2.org/2020.6/common/silva-138-99-nb-classifier.qza

Nevertheless, thanks for the new 2020.6 version!

thermokarst · June 30, 2020, 1:17pm

Thanks @Mechah! I think the URL is fixed now - please let us know if you run into any more issues. Thanks!

q2d2 · July 9, 2020, 12:14am

Yahoo! VMs are hot and fresh out of the oven:

https://docs.qiime2.org/2020.6/install/virtual/

Enjoy!

Yin_Hui_Cheok · July 16, 2020, 1:02pm

The alpha rarefaction graph still utilising metric "observed-otus", is that normal?

thermokarst · July 16, 2020, 3:19pm

Hi @Yin_Hui_Cheok!

Yes! Please see the changelog, above:

We started replacing the phrase "observed OTUs" with "observed features", however the work isn't yet complete.

fgara · July 17, 2020, 3:16pm

Dear QIIME2 developers,

Thank you so much for all of your great work!

I just have a simple question for this version please: does this version support filtering features based on their relative frequencies?

Many thanks!

ben · July 21, 2020, 2:09pm

Congratulations QIIME2 developers

thermokarst · July 21, 2020, 7:59pm

Hi @fgara! Not directly, but, you can do a little bit of manual arithmetic to figure out the threshold, if you wish to filter by relative frequency. I believe there are a few examples floating around here on the forum.