Kraken's Curse (itch) Mac OS
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Features
Kraken's Curse (itch) Mac Os Catalina
About Kraken
Kraken is a system for assigning taxonomic labels to short DNA sequences,usually obtained through metagenomic studies. Previous attempts by otherbioinformatics software to accomplish this task have often used sequencealignment or machine learning techniques that were quite slow, leading tothe development of less sensitive but much faster abundance estimationprograms. Kraken aims to achieve high sensitivity and high speed byutilizing exact alignments of k-mers and a novel classification algorithm.
In its fastest mode of operation, for a simulated metagenome of 100 bpreads, Kraken processed over 4 million reads per minute on a singlecore, over 900 times faster than Megablast and over 11 times faster than theabundance estimation program MetaPhlAn. Kraken's accuracy is comparablewith Megablast, with slightly lower sensitivity and very high precision.
Kraken is written in C++ and Perl, and is designed for use with theLinux operating system. We have also successfully compiled and run it under the Mac OS.
NOTE: Kraken 2 is the newest version of Kraken (See Kraken 2's Webpage for details). Kraken 1 will continue to be available via the Kraken 1 Github page, but it is no longer being supported.
Downloads and Documents
- Kraken 2 source code release
The current version of Kraken (v2) can be found in its GitHub repository. - The previous version of Kraken (v1) is still available in its own repository.
Note: the databases below were built for Kraken v1
- MiniKraken DB_4GB (2.9 GB): A pre-built 4 GB database constructed from complete bacterial, archaeal, and viral genomes in RefSeq (as of Oct. 18, 2017). This can be used by users without the computational resources needed to build a Kraken database. However this contains only 2.7% of kmers from the original database.
- DustMasked MiniKraken DB 4GB (2.9 GB): This 4GB database constructed from dustmasked bacterial, archaeal, and viral genomes in Refseq as of Oct. 18, 2017.
- Bracken files for this database can be found at https://ccb.jhu.edu/software/bracken/
- seqid2taxid.map (11 MB)
- MiniKraken DB_8GB (6.0 GB): A pre-built 8 GB database constructed from complete bacterial, archaeal, and viral genomes in RefSeq (as of Oct. 18, 2017). This can be used by users without the computational resources needed to build a Kraken database. This contains around 5% of kmers from the original standard database.
- DustMasked MiniKraken DB 8GB (6.0 GB): This 8GB database constructed from dustmasked bacterial, archaeal, and viral genomes in Refseq as of Oct. 18, 2017.
- Bracken files for this database can be found at https://ccb.jhu.edu/software/bracken/
- seqid2taxid.map (11 MB)
- Kraken's operating manual (html). Please use this guidefor installing and running Kraken.
- Accuracy data (1.8 MB): The data used to evaluate the accuracy of Kraken (and other classifiers); contains three FASTA files and instructions for obtaining the source taxonomic IDs for each sequence. These simulated metagenomic samples (each 10,000 reads) were also used to evaluate the speed of the non-Kraken classifiers.
- Timing data (1.8 GB): The data used to evaluate the speed of Kraken (and MetaPhlAn); contains three FASTA files, each containing 10,000,000 reads.
Accuracy and speed
Although we tested Kraken on real sequence data from isolated genomes,the biggest challenge for an exact alignment approach is that ofmaintaining sensitivity in the face of high divergence from the training data(in this case, Kraken's genomic library). To address the concern ofKraken's sensitivity with such sequences, we created a simulated metagenomicdataset containing simulated 100 bp reads with high sequencing error(2.1% SNP rate, 1.1% indel rate).Below are the results of using various classifiers on this dataset, withaccuracy evaluated on a per-read basis (these results used January 2013data to build each classifier's reference library):
| Classifier | Genus precision | Genus sensitivity | Speed (reads/min) |
|---|---|---|---|
| Naïve Bayes Classifier | 97.64 | 97.64 | 7 |
| PhymmBL | 96.11 | 96.11 | 76 |
| PhymmBL (conf. > 0.65) | 99.08 | 95.45 | 76 |
| Megablast w/ best hit | 96.93 | 93.67 | 4511 |
| Kraken | 99.90 | 91.25 | 1307161 |
| Kraken (quick operation) | 99.92 | 89.54 | 4101162 |
| MiniKraken 2014 (Kraken w/ 4GB DB) | 99.95 | 65.87 | 1441476 |
| MiniKraken 2014 (quick operation) | 99.98 | 65.31 | 2693119 |
| MetaPhlAn | n/a | n/a | 370770 |
Removing low-complexity sequences
When analyzing a metagenomics sample using a large Kraken database -- including the standardDB described in the manual -- the primary source of false positive hits is low-complexity sequences in the genomes themselves; e.g., a string of 31 or more consecutive A's. Thesecan largely be eliminated by first running the 'dust' program on all genomes and then building the database from these 'dusted' genomes. We strongly recommend running this program, which requires a custom database build, as described in the manual.DUST is included with the BLAST program from NCBI and is described inMorgulis et al. 2006 (www.ncbi.nlm.nih.gov/pubmed/16796549).
Kraken and other tools
Bracken allows users to perform abundance estimation with Kraken results. Bracken uses a bayesian formula toestimate species/genus-level abundance from Kraken classification results.
Pavianhas also been developed as a comprehensive visualization program that can compare Kraken classificationsacross multiple samples.
Kraken's Curse (itch) Mac Os X
KrakenToolsis a suite of scripts designed to assist with downstream analysis ofKraken results. KrakenTools is an ongoing project led by Jennifer Lu
Reference
Wood DE, Salzberg SL: Kraken: ultrafast metagenomic sequence classification using exact alignments. Genome Biology 2014, 15:R46.