CaSSiS specifications

Information


Unique identifier OMICS_14274
Name CaSSiS
Alternative name Comprehensive and Sensitive Signature Search
Software type Package/Module
Interface Command line interface
Restrictions to use None
Output format CSV
Operating system Unix/Linux
Programming languages C, C++
License GNU General Public License version 3.0
Computer skills Advanced
Version 0.5.2
Stability Stable
Maintained Yes

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Versioning


No version available

Documentation


Maintainer


  • person_outline Harald Meier

Publication for Comprehensive and Sensitive Signature Search

CaSSiS citations

 (2)
library_books

HTSFinder: Powerful Pipeline of DNA Signature Discovery by Parallel and Distributed Computing

2016
Evol Bioinform Online
PMCID: 4750899
PMID: 26884678
DOI: 10.4137/EBO.S35545

[…] e for the alignment of very large DNA and amino acid sequences. Furthermore, these three pipelines use Basic Local Alignment Search Tool (BLAST) for the evaluation of signatures regarding specificity.CaSSiS is an algorithm for detecting signatures with maximal group coverage within a user-defined specificity range for designing primers and probes. It provides signatures for single or group organis […]

library_books

Improving probe set selection for microbial community analysis by leveraging taxonomic information of training sequences

2011
BMC Bioinformatics
PMCID: 3224148
PMID: 21985453
DOI: 10.1186/1471-2105-12-394

[…] tational methods exist to create microarray probe sets for conserved functional genes for microbial community analysis. These include such methods as Hierarchical Probe Design, PhylArray, HiSpOD, and CaSSiS [-]. These methods seek to design probes that are group- and/or sequence-specific. PhylArray also designs degenerate and non-degenerate probes to within-group polymorphisms in an effort to dete […]

CaSSiS institution(s)
Chair of Computer Architecture, Technische Universität München, Garching, Germany; Chair of Network Architectures and Services Department of Informatics, Technische Universität München, Garching, Germany
CaSSiS funding source(s)
This work was supported by Bayerische Forschungsstiftung (AZ 767-07) and Deutsche Forschungsgemeinschaft (ENP GR 3688/1-1).

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