benkaehler / readytowear Goto Github PK
View Code? Open in Web Editor NEWReady-made Taxonomic Weights Repository
License: BSD 3-Clause "New" or "Revised" License
Ready-made Taxonomic Weights Repository
License: BSD 3-Clause "New" or "Revised" License
the tutorial should cover:
Just noticed that the V4 primers being used in the weight assembly scripts are using the old EMP primers (ex here). A few years back these were modified slightly and degeneracy added (as described here). I'm not sure if this would have any real significant effect but might be worth updating nevertheless.
Primers currently being used in weight assembly:
FWD: GTGCCAGCMGCCGCGGTAA
REV: GGACTACHVGGGTWTCTAAT
Recommended update to new EMP primers:
FWD: GTGYCAGCMGCCGCGGTAA;
REV: GGACTACNVGGGTWTCTAAT
We only have version 138 weights. 138.1 has been requested...
Howdy!
I noticed the disclaimer on the GTDB data page:
Warning: files in this directory are experimental. Many of the reference sequences appear to be in mixed orientations, which currently are not handled well by q2-feature-classifier and may yield misleading results. Use at your own risk.
Which is of course a valid concern, but this only applies to the full length refs, right? Since the V4 ones go through the extract read
process initially which correct these mixed orientations? (as per @nbokulich's note here).
Or... does extract read
's --p-read-orientation both
only apply both orientation in its search and doesn't actually correct the reads in the output?
Thanks!
Hello, I'm Hanbeen Kim.
Thank you for being so dedicated.
I have a question about "animal-proximal-gut" database.
I have studied the rumen microbiome and tried to make a weighted classifier.
Does the "animal-proximal-gut" mean rumen?
If it is not, can you advise how to make a specific database to make a weighted classifier?
I hope you have a nice day.
Hanbeen Kim.
Hi, is it possible to use silva v138.1 reference seqs and taxonomies together with class-weights available in your readytowear inventory, which are based on v138?
Thanks for this great tools!
Hello, I downloaded ref-seqs.qza using the following command:
wget -O "ref-seqs.qza" "https://github.com/BenKaehler/readytowear/blob/master/data/gg_13_8/515f-806r/ref-seqs.qza"
Then I tried running it as part of the command:
qiime feature-classifier fit-classifier-naive-bayes \
--i-reference-reads ref-seqs.qza \
--i-reference-taxonomy ref-tax.qza \
--i-class-weight human-stool.qza \
--o-classifier gg138_v4_human-stool_classifier.qza
And got the following error: " (1/1) Invalid value for '--i-reference-reads': ref-seqs.qza is not a QIIME archive."
I tried viewing the object using qiime tools peek ref-seqs.qza
and got a similar error:
"raise ValueError("%s is not a QIIME archive." % filepath)
ValueError: ref-seqs.qza is not a QIIME archive."
Interestingly, when I downloaded the file in my browser and tried viewing it on the QIIME2 website it was able to interpret it ("DNASequencesDirectoryFormat" format file of type "FeatureData[Sequence]"). Do you have any idea what might be going wrong or if there is something wrong with the file? Thanks!
Hello there,
Quick questions,
Cheers,
Luis Alfonso.
The GTDB release is getting a bit long in the tooth. We’re now two releases out of date.
Hoping you can help clarify which taxonomic weight .qza file to use for mouse fecal samples. Animal-distal-gut or animal-secretion?
PR #8 did not include scripts for generating the human vaginal weights.
Those scripts must be added.
Hello,
I am doing microbiome analysis on samples from tenrecs. I am curious what animals are represented by the animal distal gut weights and if you think this file would be appropriate to use on my samples since the tenrec group is likely poorly represented in reference databases.
Thank you!
searchable inventory of readytowear weights, listing:
name (sample type)
reference database
primers
redbiom search terms?
see mockrobiota for an example
Also include a script to generate this inventory.
Would be good if we could automate checking that the weights and uploaded references can be used to build valid classifiers.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.