SHARCGS statistics

Tool stats & trends

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SHARCGS specifications

Information


Unique identifier OMICS_00029
Name SHARCGS
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Computer skills Advanced
Stability Stable
Maintained Yes

Versioning


No version available

Documentation


Maintainer


  • person_outline Heinz Himmelbauer

Publication for SHARCGS

SHARCGS citations

 (3)
library_books

A base composition analysis of natural patterns for the preprocessing of metagenome sequences

2013
BMC Bioinformatics
PMCID: 3816298
PMID: 24564274
DOI: 10.1186/1471-2105-14-S11-S5

[…] ches from probability theory, or from the memory-based, are gaining popularity. This was determined by Zhang et. al. [] who compared the performance of eight distinct tools (i.e., SSAKE, VCAKE, QSRA, SHARCGS, Edena, Velvet, SOAPdenovo, and Taipan) against eight groups of simulated datasets.In metagenomic studies, where there are different kinds of reads or contigs mixed together into the same pool […]

library_books

Evaluating the Fidelity of De Novo Short Read Metagenomic Assembly Using Simulated Data

2011
PLoS One
PMCID: 3100316
PMID: 21625384
DOI: 10.1371/journal.pone.0019984

[…] s. The greedy algorithm used by CAP3 , Phrap and TIGR assembler is conceptually the simplest solution to genome assembly and new tools tailored to NGS data have been developed recently like SSAKE , SHARCGS or VCAKE . But maybe the most popular algorithmic solution is the Overlap-Layout-Consensus (OLC) algorithm used in the Celera Assembler , Arachne , , PCAP or Mira to name a few. With the con […]

library_books

Large scale single nucleotide polymorphism discovery in unsequenced genomes using second generation high throughput sequencing technology: applied to turkey

2009
BMC Genomics
PMCID: 2772860
PMID: 19835600
DOI: 10.1186/1471-2164-10-479

[…] For the actual SNP detection, a required reference genome was constructed by first performing de novo short read sequence assembly. Available de novo assemblers were SSAKE [], SHARCGS [], Edena [], Velvet [], and ALLPATHS []. Likely because of the large genome target and relatively high error rate of 1% ALLPATHS and SHARCGS showed an unfeasible large memory footprint and ru […]

Citations

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SHARCGS institution(s)
Max-Planck-Institute for Molecular Genetics, Berlin-Dahlem, Germany; Institute for Functional Genomics, Computational Diagnostics, University of Regensburg, Regensburg, Germany

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