:: DESCRIPTION
KCOSS is used to count the sequence files in FASTA format and save the statistical results as binary files to save space.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation:
Tang D, Li Y, Tan D, Fu J, Tang Y, Lin J, Zhao R, Du H, Zhao Z.
KCOSS: an ultra-fast k-mer counter for assembled genome analysis.
Bioinformatics. 2021 Nov 26:btab797. doi: 10.1093/bioinformatics/btab797. Epub ahead of print. PMID: 34849595.
:: DESCRIPTION
GECKO is a genetic algorithm toclassify and extract meaningful sequences from multiple types of sequencing approaches including mRNA, microRNA, and DNA methylome data.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Thomas A, Barriere S, Broseus L, Brooke J, Lorenzi C, Villemin JP, Beurier G, Sabatier R, Reynes C, Mancheron A, Ritchie W.
GECKO is a genetic algorithm to classify and explore high throughput sequencing data.
Commun Biol. 2019 Jun 20;2:222. doi: 10.1038/s42003-019-0456-9. PMID: 31240260; PMCID: PMC6586863.
:: DESCRIPTION
Turtle is a novel method that balances time, space and accuracy requirements to efficiently extract frequent k-mers even for high coverage libraries and large genomes such as human.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Roy, Rajat S. and Bhattacharya, Debashish and Schliep , Alexander.
Turtle: Identifying frequent k-mers with cache-efficient algorithms
Bioinformatics. 2014 Apr 2.
:: DESCRIPTION
SKESA is a de-novo sequence read assembler for microbial genomes. It uses conservative heuristics and is designed to create breaks at repeat regions in the genome.
::DEVELOPER
NCBI – National Center for Biotechnology Information
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Souvorov A, Agarwala R.
SAUTE: sequence assembly using target enrichment.
BMC Bioinformatics. 2021 Jul 21;22(1):375. doi: 10.1186/s12859-021-04174-9. PMID: 34289805; PMCID: PMC8293564.
Souvorov A, Agarwala R, Lipman DJ.
SKESA: strategic k-mer extension for scrupulous assemblies.
Genome Biol. 2018 Oct 4;19(1):153. doi: 10.1186/s13059-018-1540-z. PMID: 30286803; PMCID: PMC6172800.
:: DESCRIPTION
Phy-Mer is a novel alignment-free and reference-independent mitochondrial haplogroup classifier.
::DEVELOPER
MEEI Bioinformatics Center (MBC)
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Phy-Mer: a novel alignment-free and reference-independent mitochondrial haplogroup classifier.
Navarro-Gomez D, Leipzig J, Shen L, Lott M, Stassen AP, Wallace DC, Wiggs JL, Falk MJ, van Oven M, Gai X.
Bioinformatics. 2014 Dec 12. pii: btu825
:: DESCRIPTION
BFCounter is a program for counting k-mers from DNA sequencing data it uses a Bloom filter data structure to filter unique k-mers, likely generated from sequencing errors. Counting k-mers (substrings of length k) is an essential compononet of many methods in bioinformatics, including for genome and transcriptome assembly, for metagenomic sequencing, and for error correction of sequence reads. Although simple in principle, counting k-mers in large modern sequence data sets can easily overwhelm the memory capacity of standard computers. In current data sets, a large fraction – often more than 50% – of the storage capacity may be spent on storing k-mers that contain sequencing errors and which are typically observed only a single time in the data. These singleton k-mers are uninformative for many algorithms without some kind of error correction.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Melsted, P. and Pritchard, J.K.:
Efficient counting of k-mers in DNA sequences using a bloom filter
BMC Bioinformatics 2011 12:333.
:: DESCRIPTION
PLEK uses an improved computational pipeline based on k-mer and support vector machine (SVM) to distinguish long non-coding RNAs (lncRNAs) from messager RNAs (mRNAs).
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation:
BMC Bioinformatics. 2014 Sep 19;15:311. doi: 10.1186/1471-2105-15-311.
PLEK: a tool for predicting long non-coding RNAs and messenger RNAs based on an improved k-mer scheme.
Li A, Zhang J1, Zhou Z..
:: DESCRIPTION
KMC is a utility designed for counting k-mers (sequences of consecutive k symbols) in a set of reads from genome sequencing projects.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
S. Deorowicz, M. Kokot, Sz. Grabowski, A. Debudaj-Grabysz,
KMC 2: Fast and resource-frugal k-mer counting.
Bioinformatics. 2015 Jan 20. pii: btv022.
S. Deorowicz, A. Debudaj-Grabysz, Sz. Grabowski,
Disk-based k-mer counting on a PC.
BMC Bioinformatics 2013, 14:160. doi:10.1186/1471-2105-14-160
:: DESCRIPTION
DSK is a k-mer counting software, similar to Jellyfish. Jellyfish is very fast but limited to large-memory servers and k ≤ 32. In contrast, DSK supports large values of k, and runs with (almost-)arbitrarily low memory usage and reasonably low temporary disk usage. DSK can count k-mers of large Illumina datasets on laptops and desktop computers.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
DSK: k-mer counting with very low memory usage.
Rizk G, Lavenier D, Chikhi R.
Bioinformatics. 2013 Mar 1;29(5):652-3. doi: 10.1093/bioinformatics/btt020. Epub 2013 Jan 16.
:: DESCRIPTION
KmerGenie estimates the best k-mer length for genome de novo assembly. Given a set of reads, KmerGenie first computes the k-mer abundance histogram for many values of k. Then, for each value of k, it predicts the number of distinct genomic k-mers in the dataset, and returns the k-mer length which maximizes this number. Experiments show that KmerGenie’s choices lead to assemblies that are close to the best possible over all k-mer lengths.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation:
Bioinformatics. 2014 Jan 1;30(1):31-7. doi: 10.1093/bioinformatics/btt310. Epub 2013 Jun 3.
Informed and automated k-mer size selection for genome assembly.
Chikhi R1, Medvedev P.
