Tag: K-mers

Merqury v1.3 – Evaluate Genome Assemblies with k-mers

Merqury v1.3

:: DESCRIPTION

Merqury is a novel tool for reference-free assembly evaluation based on efficient k-mer set operations.

::DEVELOPER

Maryland Bioinformatics Labs (MarBL)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

Merqury

:: MORE INFORMATION

Citation

Rhie A, Walenz BP, Koren S, Phillippy AM.
Merqury: reference-free quality, completeness, and phasing assessment for genome assemblies.
Genome Biol. 2020 Sep 14;21(1):245. doi: 10.1186/s13059-020-02134-9. PMID: 32928274; PMCID: PMC7488777.

RAMBO-K 1.21 – Read Assignment Method Based On K-mers

RAMBO-K 1.21

:: DESCRIPTION

RAMBO-K is a reference-based tool for rapid and sensitive extraction of one organisms reads from a mixed dataset.

::DEVELOPER

RAMBO-K team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • Java
  • Python

:: DOWNLOAD

 RAMBO-K 

:: MORE INFORMATION

Citation

RAMBO-K: Rapid and Sensitive Removal of Background Sequences from Next Generation Sequencing Data.
Tausch SH, Renard BY, Nitsche A, Dabrowski PW.
PLoS One. 2015 Sep 17;10(9):e0137896. doi: 10.1371/journal.pone.0137896.

MetaCon – Unsupervised Clustering of Metagenomic Contigs with Probabilistic k-mers Statistics and Coverage

MetaCon

:: DESCRIPTION

MetaCon is a novel tool for unsupervised metagenomic contig binning based on probabilistic k-mers statistics and coverage.

::DEVELOPER

Matteo Comin

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

MetaCon

:: MORE INFORMATION

Citation

BMC Bioinformatics, 20 (Suppl 9), 367 2019 Nov 22
MetaCon: Unsupervised Clustering of Metagenomic Contigs With Probabilistic K-Mers Statistics and Coverage
Jia Qian, Matteo Comin

SKraken – Classification of Short Metagenomic Reads based on filtering uninformative k-mers

SKraken

:: DESCRIPTION

SKraken is an efficient approach to accurately classify metagenomic reads against a set of reference genomes, e.g. the NCBI/RefSeq database.

::DEVELOPER

Matteo Comin

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

SKraken

:: MORE INFORMATION

Citation

D. Marchiori, M. Comin
“SKraken: Fast and Sensitive Classification of Short Metagenomic Reads based on Filtering Uninformative k-mers“.
In Proceedings of the 10th International Conference on Bioinformatics Models, Methods and Algorithms (Bioinformatics 2017), pp. 59-67

ShortCAKE – Shortest sequence to Cover All K-mErs

ShortCAKE

:: DESCRIPTION

ShortCAKE is a software for generating a shortest sequence that for each DNA k-mer includes the k-mer or its reverse complement. In other words, it generates a shortest possible double-stranded sequence covering all k-mers.

::DEVELOPER

Ron Shamir’s lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

  ShortCAKE

:: MORE INFORMATION

Citation

Design of Shortest Double-Stranded DNA Sequences Covering All K-mers with Applications to Protein Binding Microarrays and Synthetic Enhancers,
Yaron Orenstein, Ron Shamir.
Vol. 29 (13), Pages i71-i79, Bioinformatics (2013).doi: 10.1093/bioinformatics/btt230

Jellyfish 2.3.0 – Counting of K-mers in DNA

Jellyfish 2.3.0

:: DESCRIPTION

JELLYFISH is a tool for fast, memory-efficient counting of k-mers in DNA. A k-mer is a substring of length k, and counting the occurrences of all such substrings is a central step in many analyses of DNA sequence. JELLYFISH can count k-mers using an order of magnitude less memory and an order of magnitude faster than other k-mer counting packages by using an efficient encoding of a hash table and by exploiting the “compare-and-swap” CPU instruction to increase parallelism.

::DEVELOPER

Kingsford Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 JELLYFISH

:: MORE INFORMATION

Citation

Bioinformatics. 2011 Mar 15;27(6):764-70. doi: 10.1093/bioinformatics/btr011. Epub 2011 Jan 7.
A fast, lock-free approach for efficient parallel counting of occurrences of k-mers.
Marçais G, Kingsford C.