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The RDPClassifier is a naive Bayesian classifier that can rapidly and accurately provides taxonomic assignments for bacterial and archaeal 16S rRNA sequences, fungal LSU and fungal ITS sequences, with confidence estimates for each assignment. More information and tutorials on how to install, use and retrain RDP Clasifier can be found on at https://github.com/rdpstaff/classifier and John Quensen's blog (https://john-quensen.com/).
A Fast QR code detector for arbitrarily acquired images
...This project implements a two-stage component-based approach to perform accurate detection of QR code symbols in arbitrarily acquired images. In the first stage a cascade classifier to detect parts of the symbol is trained using the rapid object detection framework proposed by Viola-Jones. In the second stage, detected patterns are aggregated in order to evaluate if they are spatially arranged in a way that is geometrically consistent with the components of a QR code symbol. OpenCV 2.2+ is required.
A set of scripts (mostly python) for processing reads generated by the Roche 454 or Illumina next-gen sequencing platforms. Included are quality control, read demultiplexing and microbiome characterisation scripts for use with usearch, pplacer and RDPclassifier.
The package was used to produce the data presented in Smith et al. (2012) "The Cervical Microbiome over 7 Years and a Comparison of Methods for its Characterization".