The khmer software package: enabling efficient nucleotide sequence analysis
نویسندگان
چکیده
The khmer package is a freely available software library for working efficiently with fixed length DNA words, or k-mers. khmer provides implementations of a probabilistic k-mer counting data structure, a compressible De Bruijn graph representation, De Bruijn graph partitioning, and digital normalization. khmer is implemented in C++ and Python, and is freely available under the BSD license at https://github.com/dib-lab/khmer/.
منابع مشابه
These Are Not the K-mers You Are Looking For: Efficient Online K-mer Counting Using a Probabilistic Data Structure
K-mer abundance analysis is widely used for many purposes in nucleotide sequence analysis, including data preprocessing for de novo assembly, repeat detection, and sequencing coverage estimation. We present the khmer software package for fast and memory efficient online counting of k-mers in sequencing data sets. Unlike previous methods based on data structures such as hash tables, suffix array...
متن کاملWalking the Talk: Adopting and Adapting Sustainable Scientific Software Development processes in a Small Biology Lab
The khmer software project provides both research and production functionality for largescale nucleic-acid sequence analysis. The software implements several novel data structures and algorithms that perform data pre-fltering for common bioinformatics tasks, including sequence mapping and de novo assembly. Development is driven by a small lab with one full-time developer (MRC), as well as sever...
متن کاملEfficient cardinality estimation for k-mers in large DNA sequencing data sets
We present an open implementation of the HyperLogLog cardinality estimation sketch for counting fixed-length substrings of DNA strings (“k-mers”). The HyperLogLog sketch implementation is in C++ with a Python interface, and is distributed as part of the khmer software package. khmer is freely available from https://github.com/dib-lab/khmer under a BSD License. The features presented here are in...
متن کاملCrossing the streams: a framework for streaming analysis of short DNA sequencing reads
5 We present a semi-streaming algorithm for k-mer spectral analysis of 6 DNA sequencing reads, together with a derivative approach that is fully 7 streaming. The approach can also be applied to genomic, transcriptomic, 8 and metagenomic data sets. We develop two tools for short-read analysis 9 based on these approaches, a method for semi-streaming k-mer-based error 10 trimming, and a method for...
متن کاملFFBSKAT: Fast Family-Based Sequence Kernel Association Test
The kernel machine-based regression is an efficient approach to region-based association analysis aimed at identification of rare genetic variants. However, this method is computationally complex. The running time of kernel-based association analysis becomes especially long for samples with genetic (sub) structures, thus increasing the need to develop new and effective methods, algorithms, and ...
متن کامل