103 Release the Kraken

Micro binfie podcast

We are talking about KRAKEN - the taxonomic classification software and in the hot seat are Dr Jennifer Lu and Natalia Rincon from Johns Hopkins University Center for Computational Biology. The MicroBinfie podcast welcomed Dr. Jennifer Lu and Natalia Rincon to discuss Kraken, a taxonomic classification software. Developed in 2013-2014, Kraken easily identifies and assigns sequencing reads to a specific species, genus, or general bacteria. Its efficiency in classifying millions or billions of reads puts it ahead of other classification methods such as Melan, Mega Blast, and Chime. The tool is known for its ease of use and accuracy. Following the success of Kraken's metagenomic analysis, Florian Breitweiser developed Kraken Unique, which provides more information than the standard Kraken. C Another edition to the Kraken family is Bracken, developed by Jennifer Lu, which estimates abundance, and Nat Rincon contributes to the newest editions, which analyze diversity metrics. Kraken's exact camera matching technology identifies reads and classifies taxonomy IDs, with two outputs: a long text file for every read and a Kraken report that provides a breakdown of reads for each taxonomy ID. The interpretation of the Kraken report relies on the sample and its taxon. Even if there are few reads available, taxons can still be meaningful. For beginners, Kraken simplifies the classification process by providing pre-built databases. There was an interesting discussion about the origin of the Kraken name. It is derived from a mythological creature that relied on Jellyfish, a camera counting tool used to build the Kraken databases. Derek Wood developed the original concept of Kraken. The hosts found a true pathogen in a sample, which was significant for downstream analysis. The number of reads in some samples was very few, and some unclassified reads could also be uninformative or indicate contamination. Being developed for Illumina reads, Kraken's accuracy in classifying Nanopore reads is likely to be affected due to the higher error rate. The Kraken database achieves exact matching of k-mers and fits all genome information into a small space. Tools spawned out of the Kraken world are widely used due to their high accuracy, speed, and simplicity in the classification of taxonomy. Kraken provides an additional column in the report to count the number of unique k-mers to validate the results. The developers worked closely with others to test new Nanopore chemistries due to the frequent changes in the chemistry that affected the accuracy of the reads. Kraken databases contain vector sequence information, and vectors are given their taxonomy ID as "synthetic sequences." The software mixes Pearl and C++, with Pearl processing inputs and C++ managing heavy memory stuff by building and compacting sequences and writing bytes. Dr. Jennifer Lu appreciates the simplicity and accuracy of the classification algorithm, and Nat Rincon takes pride in being part of the Kraken community.