UNITE (ver 7.2 2017-12-01) Classifiers for QIIME2 (ver. 2017.12) Available Here

Hello everyone,

Because some people (myself included) were having a hard time training their UNITE classifiers for fungal ITS data due to memory errors, I am making my two classifiers available here for anyone who would like to use them (links created with the help of @gregcaporaso).

99% Classifier:
UNITE ver 7.2 99% Classifier

Dynamic Classifier:
UNITE ver 7.2 Dynamic Classifier

Some pertinent information:

  1. There are two classifiers available. One uses a 99% threshold for clustering and the other is ‘dynamic,’ meaning it uses either a 97% or 99% threshold (or somewhere in between) based on which is more accurate for certain lineages of fungi (as determined manually by experts in the field).

  2. The version of UNITE I used is the most current (version 7.2, release date 2017-12-01). I retrieved it from the following site: https://doi.org/10.15156/BIO/587481

  3. I used the most current version of QIIME2 to create the classifiers (2017.12), and I followed a protocol posted previously on GitHub, just updating the source files: https://github.com/gregcaporaso/2017.06.23-q2-fungal-tutorial

  4. The classifiers were created without a “feature-classifier extract-reads” command so they should work well for any primer sets. According to @Nicholas_Bokulich, with fungal ITS data we see a performance decrease when the feature classifier is trained on extracted sequence reads. See this post for more info: https://forum.qiime2.org/t/memoryerror-when-training-unite-ver7-01-12-2017-classifier/2757/2

Please don’t hesitate to contact me if there’s any other information you need!

Sydney

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You’ve saved my day :slight_smile: Thank you.
Just wondering, how powerful PC was required to train this classifier ?

@Jaroslaw_Grzadziel,

Here are the specs for the computer I used to generate these classifiers:

OS: Linux 3.10.0-693.11.1.el7.x86_64 x86_64
System: Red Hat Enterprise Linux Workstation release 7.4 (Maipo)
Processor (CPU): Intel® Core™ i7-4790 CPU @ 3.60GHz
Speed: 3,603.66 MHz
Cores: 8
Memory (RAM): 15.6 GB

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