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SSAKE specifications


Unique identifier OMICS_00033
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Computer skills Advanced
Stability Stable
Maintained Yes




No version available


  • person_outline Rene Warren

Publication for SSAKE

SSAKE citations


A Comprehensive Study of De Novo Genome Assemblers: Current Challenges and Future Prospective

Evol Bioinform Online
PMCID: 5826002
PMID: 29511353
DOI: 10.1177/1176934318758650

[…] an genome fraction of 48.7%, 44.3%, and 43.8%. On eukaryotic paired-end data sets, Edena showed highest genome fraction with a mean of 90.4% and the second highest Velvet with a mean of 85.6% whereas SSAKE showed lowest genome fraction with a mean of 49.2% and 74.0% in single-end and paired-end data sets (). Practically, an assembler which produces the fewer number of contigs, with high N50 and hi […]


Genome assembly of the Pink Ipê (Handroanthus impetiginosus, Bignoniaceae), a highly valued, ecologically keystone Neotropical timber forest tree

PMCID: 5905499
PMID: 29253216
DOI: 10.1093/gigascience/gix125

[…] NA; PASA: Program to Assemble Spliced Alignment; REAPR: Recognition of Errors in Assemblies using Paired Reads; SINE: short interspersed nuclear elements; SNP: single nucleotide polymorphism; SSPACE: SSAKE-based Scaffolding of Pre-Assembled Contigs after Extension; TE: transposable element. […]


The long reads ahead: de novo genome assembly using the MinION

PMCID: 5770995
PMID: 29375809
DOI: 10.5256/f1000research.12992.r24090

[…] LC-based methods, but proved faster in some cases . A selection of available long read OLC and DBG assemblers is discussed in this section.Software using traditional greedy extension algorithms (e.g. SSAKE) is rarely used in MinION read assembly as it was found to perform decidedly less well in a de novo assembly setting, both in terms of assembly quality and required computational resources , and […]


Mitochondrial genome evolution in Alismatales: Size reduction and extensive loss of ribosomal protein genes

PLoS One
PMCID: 5435185
PMID: 28545148
DOI: 10.1371/journal.pone.0177606
call_split See protocol

[…] ST/). Consensus sequences of each contig were used as seed sequences and extended using both 454 reads and Illumina reads in the Short Sequence Assembly by K-mer search and 3' read Extension program, SSAKE ver. 3.5 [], with parameters -m 15 -o 2 -r 0.6 -p 0 -t 0 -v 1. Finally, all 454 and Illumina reads where mapped to the assembled mitogenomes using Geneious ver. 7.1 (Biomatters Ltd.) to verify t […]


First Draft Genome Sequence of the Dourine Causative Agent: Trypanosoma Equiperdum Strain OVI

J Genomics
PMCID: 5278650
PMID: 28138343
DOI: 10.7150/jgen.17904

[…] version 1.2.03 with a range of k-mer values from 25 to 85. Assembled contigs of less than 1,000 bp were disregarded. Contigs of the best assembly, provided by k-mer length of 33, were extended with SSAKE (default parameter values) using Velvet generated contigs as “seeds” and the short-reads unused by Velvet for their extension . The genome was assembled into 2,026 contigs (>1000 bp) giving a co […]


Approaches for in silico finishing of microbial genome sequences

Genet Mol Biol
PMCID: 5596377
PMID: 28898352
DOI: 10.1590/1678-4685-GMB-2016-0230

[…] tp://, and is developed to work on the Linux operating system.SOPRA (): This scaffolding tool was designed to improve assemblies generated by Velvet () and SSAKE (), and targets the earlier sequencing platforms from Illumina and ABI SOLiD. The program parses the read-placing file generated by these assemblers and extracts information of paired-end/mate-p […]


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SSAKE institution(s)
British Columbia Cancer Agency, Genome Sciences Centre, Vancouver, Canada; J. Craig Venter Institute, Rockville, MD, USA

SSAKE reviews

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Anonymous user #26098

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The best short read assembler I could find!
Anonymous user #48's avatar image No country

Anonymous user #48

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Ssake is super easy to use and produces accurate results.
It is lightweight and has no dependencies, I highly recommend it. Because it uses coverage info, assemblies are stratified which makes it also suitable for transcriptome and meta genome assemblies. It is not as greedy as most people report, the correct path is chosen no based on longest overlap, but coverage and reads having a matching pairing partner already assembled