Version Differences for CISA

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= Contig Integrator for Sequence Assembly =

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[http://www.example.com link title]= Contig Integrator for Sequence Assembly =

Recently, technological advances have dramatically improved throughput and quality of next-generation sequencing (NGS), and, in parallel with these improvements, numerous algorithms have been proposed for ''de novo'' sequence assembly. Compared to the traditional Sanger sequencing technology, NGS technologies offer several distinct features, such as large volumes of reads and concise length. In order to tackle the sequence assembly problem from a collection of short-sequencing reads of randomly sampled fragments, two types of algorithm, the overlap-layout-consensus approach and the de Bruijn graph, are commonly utilized (Paszkiewicz and Studholme 2010; Aerts, Narzisi et al. 2011). Although assemblers are generally based on a small number of algorithms, they differ from each other in terms of dealing with errors, inconsistencies, and ambiguities. Moreover, no individual assembler guarantees the best assembly for diverse species. Therefore, the use of various parameter settings and assemblers in an iterative manner to produce an improved draft assembly is inevitable. Nevertheless, few efforts have been made to integrate various assemblies into a draft that is marked by superior contiguity and accuracy. To the best of our knowledge, five tools, including GAA (Yao, Ye et al. 2012), GAM (Casagrande, Del Fabbro et al. 2009), MAIA (Nijkamp, Winterbach et al. 2010), minimus2 (Sommer, Delcher et al. 2007) and Reconciliator (Zimin, Smith et al. 2008), have been published for merging assemblies. However, GAM and Reconciliator require the original reads and complicated prerequisites; we therefore compared our proposed method with GAA, MAIA and minimus2.

In this study, state-of-the-art assemblers were used to generate different sets of contigs for bacterial genomes. We have developed and built a Contig Integrator for Sequence Assembly (CISA) to integrate the sets of contigs from different assemblers, and have evaluated the quality of our integrated assembly. Compared with the assemblies generated by each individual assembler and assembly integrator, the hybrid assembly integrated by CISA exhibits superior contiguity and accuracy.

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This work has been published in ([http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0060843 | PlOS ONE).

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This work has been published in [http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0060843 PlOS ONE] [http://www.example.com link title]).

= A schematic overview of CISA =

[[Image:Overview.jpg|left|]]

-								= Contig Integrator for Sequence Assembly =
+								[http://www.example.com link title]= Contig Integrator for Sequence Assembly =
 Recently, technological advances have dramatically improved throughput and quality of next-generation sequencing (NGS), and, in parallel with these improvements, numerous algorithms have been proposed for ''de novo'' sequence assembly. Compared to the traditional Sanger sequencing technology, NGS technologies offer several distinct features, such as large volumes of reads and concise length. In order to tackle the sequence assembly problem from a collection of short-sequencing reads of randomly sampled fragments, two types of algorithm, the overlap-layout-consensus approach and the de Bruijn graph, are commonly utilized (Paszkiewicz and Studholme 2010; Aerts, Narzisi et al. 2011). Although assemblers are generally based on a small number of algorithms, they differ from each other in terms of dealing with errors, inconsistencies, and ambiguities. Moreover, no individual assembler guarantees the best assembly for diverse species. Therefore, the use of various parameter settings and assemblers in an iterative manner to produce an improved draft assembly is inevitable. Nevertheless, few efforts have been made to integrate various assemblies into a draft that is marked by superior contiguity and accuracy. To the best of our knowledge, five tools, including GAA (Yao, Ye et al. 2012), GAM (Casagrande, Del Fabbro et al. 2009), MAIA (Nijkamp, Winterbach et al. 2010), minimus2 (Sommer, Delcher et al. 2007) and Reconciliator (Zimin, Smith et al. 2008), have been published for merging assemblies. However, GAM and Reconciliator require the original reads and complicated prerequisites; we therefore compared our proposed method with GAA, MAIA and minimus2.
 	In this study, state-of-the-art assemblers were used to generate different sets of contigs for bacterial genomes. We have developed and built a Contig Integrator for Sequence Assembly (CISA) to integrate the sets of contigs from different assemblers, and have evaluated the quality of our integrated assembly. Compared with the assemblies generated by each individual assembler and assembly integrator, the hybrid assembly integrated by CISA exhibits superior contiguity and accuracy.
-								This work has been published in ([http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0060843 | PlOS ONE).
+								This work has been published in [http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0060843 PlOS ONE] [http://www.example.com link title]).
 = A schematic overview of CISA =
 [[Image:Overview.jpg|left|]]