Identifies the relative frequencies of reference sequences contributing to a pooled DNA sample. Karp combines the speed and low-memory requirements of k-mer based pseudoalignment with a likelihood framework that uses base quality information to better resolve multiply mapped reads. It is accurate across a variety of read lengths and when samples contain reads originating from organisms absent from the reference. Karp employs an Expectation Maximization (EM) algorithm that uses information from all the reads to accurately estimate the relative frequencies of each reference in the sample.

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Karp classification

Karp specifications

Software type:
Package
Restrictions to use:
None
Input format:
FASTQ, FASTA
Programming languages:
C++
Stability:
Stable
Interface:
Command line interface
Input data:
reference sequences, taxonomy with labels corresponding to the references
Operating system:
Unix/Linux
Computer skills:
Advanced

Credits

Publications

  • (Reppell and Novembre, 2017) Using pseudoalignment and base quality to accurately quantify microbial community composition. bioRxiv.
    DOI: 10.1101/097949

Institution(s)

Department of Human Genetics, University of Chicago, Chicago, IL, USA

Funding source(s)

This work was supported by NIH/NHGRI R01 HG007089.

Link to literature

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