Eukaryote RbcL Reference Set For The RDP Classifier

This repository contains training sets that can be used with the Ribosomal Database Project classifier (Wang et al., 2007) to taxonomically assign Eukaryote rbcL cpDNA sequences including plants. The latest release can be downloaded from https://github.com/terrimporter/rbcLClassifier/releases . The trained files ready to be used with the RDP Classifier are available as well as the original files used for training (a taxonomy file and a FASTA file) are available as 'version-ref'. A diatom-specific rbcL classifier is also available at https://github.com/terrimporter/rbcLdiatomClassifier .

How to cite

You can cite this repository directly:
Teresita M. Porter. (2020, January 14). Eukaryote RbcL Reference Set For The RDP Classifier (Version v1.0.1). Zenodo. http://doi.org/10.5281/zenodo.4741459

You should also cite the Ribosomal Database Classifier:
Wang et al. (2007) Naïve Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Applied and Environmental Microbiology, 73: 5261.

Quick Start

############ Install the RDP classifier if you need it
# The easiest way to install the RDP classifier v2.13 is using conda
conda install -c bioconda rdp_classifier
# Alternatively, you can install from SourceForge and run with java if you don't use conda
wget https://sourceforge.net/projects/rdp-classifier/files/rdp-classifier/rdp_classifier_2.13.zip
# decompress it
unzip rdp_classifier_2.13
# record path to classifier.jar ex. /path/to/rdp_classifier_2.13/dist/classifier.jar

############ Get the latest rbcL training set
wget https://github.com/terrimporter/rbcLClassifier/releases/download/v1/rbcLv1_trained.tar.gz

# decompress it
tar -xzf rbcLv1_trained.tar.gz

# record the path to the rRNAClassifier.properties file ex. /path/to/mydata_trained/rRNAClassifier.properties

############ Run the RDP Classifier 
# If it was installed using conda, run it like this:
rdp_classifier -Xmx8g classify -t /path/to/mydata_trained/rRNAClassifier.properties -o rdp.output query.fasta
# Otherwise run it using java like this:
java -Xmx8g -jar /path/to/rdp_classifier_2.13/classifier.jar -t /path/to/mydata_trained/rRNAClassifier.properties -o rdp.output query.fasta

Releases

v1

The rbcLv1_trained.tar.gz file should be decompressed and used directly with the RDP Classifier to make taxonomic assignments.

RbcL records were mined from the NCBI nucleotide database [Jan. 10/20]. Sequences were filtered to retain only those that are 500bp+, contain no non-nucleotide characters, and have Linnean binomial species names. Sequences were screened for bacterial contaminants. Bacterial outgroup sequences were added.

Taxonomic assignment results should be filtered according to their bootstrap support values to reduce false positive assignments. Cutoffs are based on leave-one-sequence-out testing of non-singleton genera. Here we recommend MINIMUM bootstrap cutoffs according to query length and assignment rank. Assuming your query sequences are represented in the reference set, using the cutoffs presented in the first table below should ensure 99% accuracy. If you wish to cast a wider net, you can use the second table below for 95% accuracy.

Bootstrap support cutoffs, 99% accuracy:

Rank	500 bp+	400 bp	300 bp	200 bp	100 bp
Superkingdom	0	0	0	0	0
Kingdom	0	0	0	0	0
Phylum	0	0	0	0	0
Class	NA	70	NA	NA	NA
Order	NA	NA	NA	NA	NA
Family	NA	NA	NA	NA	NA
Genus	NA	NA	NA	NA	NA
Species	NA	NA	NA	NA	NA

NA = No cutoff available will result in 99% correct assignments

Bootstrap support cutoffs, 95% accuracy:

Rank	500 bp+	400 bp	300 bp	200 bp	100 bp
Superkingdom	0	0	0	0	0
Kingdom	0	0	0	0	0
Phylum	0	0	0	0	0
Class	0	0	0	0	0
Order	0	0	0	0	20
Family	0	0	0	0	50
Genus	95	NA	NA	NA	NA
Species	NA	NA	NA	NA	NA

NA = No cutoff available will result in 95% correct assignments

Bootstrap support cutoffs, 90% accuracy:

Rank	500 bp+	400 bp	300 bp	200 bp	100 bp
Superkingdom	0	0	0	0	0
Kingdom	0	0	0	0	0
Phylum	0	0	0	0	0
Class	0	0	0	0	0
Order	0	0	0	0	0
Family	0	0	0	0	0
Genus	70	70	80	95	NA
Species	NA	NA	NA	NA	NA

NA = No cutoff available will result in 90% correct assignments

Bootstrap support cutoffs, 80% accuracy:

Rank	500 bp+	400 bp	300 bp	200 bp	100 bp
Superkingdom	0	0	0	0	0
Kingdom	0	0	0	0	0
Phylum	0	0	0	0	0
Class	0	0	0	0	0
Order	0	0	0	0	0
Family	0	0	0	0	0
Genus	0	0	0	40	80
Species	NA	NA	NA	NA	NA

NA = No cutoff available will result in 80% correct assignments

v1-ref

The rbcLv1-ref_training.tar.gz file should be decompressed. The folder contains the original taxonomy and fasta files that are included here for reference only. Sequences were mined from the NCBI nucleotide database in January 2020 and only includes sequences identified to the species rank that are at least 500bp long. The sequences have been screened to remove any potential bacterial contaminant sequences. Taxonomic composition is largely Eukaryota with some Bacterial outgroup taxa.

How to use

Decompress the tar.gz file:

$ tar -xvzf FileName.tar.gz

Use with the RDP classifier:

java -Xmx8g -jar /path/to/rdp_classifier_2.12/dist/classifier.jar classify -t /path/to/rbcLversion_trained/rRNAClassifier.properties -o ClassifiedQueryFilename QueryFilename

Additional information

For additional information on how to run the RDP classifier, see the RDPclassifier 2.12 README.

The RDP classifier v2.12 can be downloaded from: https://sourceforge.net/projects/rdp-classifier/

References

Wang, Q., Garrity, G. M., Tiedje, J. M., & Cole, J. R. (2007). Naive Bayesian Classifier for Rapid Assignment of rRNA Sequences into the New Bacterial Taxonomy. Applied and Environmental Microbiology, 73(16), 5261–5267. Available from https://sourceforge.net/projects/rdp-classifier/

Acknowledgements

We acknowledge support from the Canadian federal Genomics Research & Development Initiative (GRDI), Metagenomics-Based Ecosystem Biomonitoring (Ecobiomics) project.

Last updated: May 6, 2021