Version Differences for CISA

= Contig Integrator for Sequence Assembly =

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Recently, technological advances have dramatically improved throughput and quality of next-generation sequencing (NGS), and in parallel with the improvements, many algorithms have been proposed for ''de novo'' sequence assembly. Compared to the traditional Sanger sequencing technology, the NGS technologies offer several distinct features, such as large volumes of reads and short length. In order to tackle the sequence assembly problem from a collection of short sequencing reads of randomly sampled fragments, two types of algorithms–overlap-layout-consensus approach and the de Bruijn graph–are commonly utilized. Albeit the assembler are mainly based on the small number of algorithms, they differ from each in terms of dealing with errors, inconsistencies and ambiguities. Moreover, no individual assembler guarantees the best assembly of diverse species. Performing different parameter settings or different assemblers in an iterative manner to generate a draft assembly is inevitable. Nevertheless, few efforts have been made to integrate the various assemblies into a better draft which possess superior quality in both contiguity and accuracy.

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Recently, technological advances have dramatically improved throughput and quality of next-generation sequencing (NGS), and in parallel with the improvements, many algorithms have been proposed for ''de novo'' sequence assembly. Compared to the traditional Sanger sequencing technology, the NGS technologies offer several distinct features, such as large volumes of reads and short length. In order to tackle the sequence assembly problem from a collection of short sequencing reads of randomly sampled fragments, two types of algorithms–overlap-layout-consensus approach and the de Bruijn graph–are commonly utilized. Albeit the assembler are mainly based on the small number of algorithms, they differ from each in terms of dealing with errors, inconsistencies and ambiguities. Moreover, no individual assembler guarantees the best assembly of diverse species. Performing different parameter settings or different assemblers in an iterative manner to generate a draft assembly is inevitable. Nevertheless, few efforts have been made to integrate the various assemblies into a better draft which possess superior quality in both contiguity and accuracy.

The qualities of genome assemblies are usually evaluated by their contiguity and the accuracy of contigs or scaffolds. The contiguity is a straightforward measurement by calculating the N50 length or the number of contigs/scaffolds, no need of the real genome. On the other hand, the accuracy of an assembly can be assessed based on alignment to a complete reference genome (Darling, et al., 2011). However, there is a transparent trade-off between contiguity and accuracy. In other words, an assembler trying to maximize the contiguity might provide a less accurate assembly, and vice versa. Since each assembler has its own features in addressing the reconstruction of a DNA sequence, can we take the advantages of all the assemblies to generate an integrated set of contigs?

 = Contig Integrator for Sequence Assembly =
-								<font size=4>Recently, technological advances have dramatically improved throughput and quality of next-generation sequencing (NGS), and in parallel with the improvements, many algorithms have been proposed for ''de novo'' sequence assembly. Compared to the traditional Sanger sequencing technology, the NGS technologies offer several distinct features, such as large volumes of reads and short length. In order to tackle the sequence assembly problem from a collection of short sequencing reads of randomly sampled fragments, two types of algorithms–overlap-layout-consensus approach and the de Bruijn graph–are commonly utilized. Albeit the assembler are mainly based on the small number of algorithms, they differ from each in terms of dealing with errors, inconsistencies and ambiguities. Moreover, no individual assembler guarantees the best assembly of diverse species. Performing different parameter settings or different assemblers in an iterative manner to generate a draft assembly is inevitable. Nevertheless, few efforts have been made to integrate the various assemblies into a better draft which possess superior quality in both contiguity and accuracy.<font>
+								<font size=4>Recently, technological advances have dramatically improved throughput and quality of next-generation sequencing (NGS), and in parallel with the improvements, many algorithms have been proposed for ''de novo'' sequence assembly. Compared to the traditional Sanger sequencing technology, the NGS technologies offer several distinct features, such as large volumes of reads and short length. In order to tackle the sequence assembly problem from a collection of short sequencing reads of randomly sampled fragments, two types of algorithms–overlap-layout-consensus approach and the de Bruijn graph–are commonly utilized. Albeit the assembler are mainly based on the small number of algorithms, they differ from each in terms of dealing with errors, inconsistencies and ambiguities. Moreover, no individual assembler guarantees the best assembly of diverse species. Performing different parameter settings or different assemblers in an iterative manner to generate a draft assembly is inevitable. Nevertheless, few efforts have been made to integrate the various assemblies into a better draft which possess superior quality in both contiguity and accuracy.</font>
 <font size=4>The qualities of genome assemblies are usually evaluated by their contiguity and the accuracy of contigs or scaffolds. The contiguity is a straightforward measurement by calculating the N50 length or the number of contigs/scaffolds, no need of the real genome. On the other hand, the accuracy of an assembly can be assessed based on alignment to a complete reference genome (Darling, et al., 2011). However, there is a transparent trade-off between contiguity and accuracy. In other words, an assembler trying to maximize the contiguity might provide a less accurate assembly, and vice versa. Since each assembler has its own features in addressing the reconstruction of a DNA sequence, can we take the advantages of all the assemblies to generate an integrated set of contigs?</font>