KMC 3: counting and manipulating k-mer statistics
نویسندگان
چکیده
Summary Counting all k -mers in a given dataset is a standard procedure in many bioinformatics applications. We introduce KMC3, a significant improvement of the former KMC2 algorithm together with KMC tools for manipulating k -mer databases. Usefulness of the tools is shown on a few real problems. Availability and implementation Program is freely available at http://sun.aei.polsl.pl/REFRESH/kmc . Contact [email protected]. Supplementary information Supplementary data are available at Bioinformatics online.
منابع مشابه
KMC 2: fast and resource-frugal k-mer counting
MOTIVATION Building the histogram of occurrences of every k-symbol long substring of nucleotide data is a standard step in many bioinformatics applications, known under the name of k-mer counting. Its applications include developing de Bruijn graph genome assemblers, fast multiple sequence alignment and repeat detection. The tremendous amounts of NGS data require fast algorithms for k-mer count...
متن کاملThese 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 کاملSqueakr: an exact and approximate k-mer counting system
Motivation k-mer-based algorithms have become increasingly popular in the processing of high-throughput sequencing data. These algorithms span the gamut of the analysis pipeline from k-mer counting (e.g. for estimating assembly parameters), to error correction, genome and transcriptome assembly, and even transcript quantification. Yet, these tasks often use very different k-mer representations ...
متن کاملDSK: k-mer counting with very low memory usage
SUMMARY Counting all the k-mers (substrings of length k) in DNA/RNA sequencing reads is the preliminary step of many bioinformatics applications. However, state of the art k-mer counting methods require that a large data structure resides in memory. Such structure typically grows with the number of distinct k-mers to count. We present a new streaming algorithm for k-mer counting, called DSK (di...
متن کاملMining K-mers of Various Lengths in Biological Sequences
Counting the occurrence frequency of each k-mer in a biological sequence is an important step in many bioinformatics applications. However, most k-mer counting algorithms rely on a given k to produce single-length k-mers, which is inefficient for sequence analysis for different k. Moreover, existing k-mer counters focus more on DNA sequences and less on protein ones. In practice, the analysis o...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Bioinformatics
دوره 33 17 شماره
صفحات -
تاریخ انتشار 2017