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Evaluation of CloudRS Algorithm with De Novo Assemblers
Objectives: The paper documents a comparative analytical study of the two prominent De Novo Algorithms (DNA) namely Velvet and SSAKE, both are being pipelined by CloudRS. Methods/Statistical Analysis: The Research process conducted in this project primarily utilized Next-Generation Sequencing data results. These data sets were further error corrected by pipelining them with CloudRS. Upon error correction, the data sets were assembled separately by VELVET and SSAKE; the data from the analysis were then analyzed as per the mathematical results produced in order to statistically compare the two algorithms for a similar environment. Findings: On assembling the error corrected genome, the data produced sets of values. These values were tabulated and noted in order to ensure effective comparison. The values being compared were the N50 and corrected lengths of the assembled genes. The general genome analysis comparison metrics were then utilized to compare the documented data. This showed that a higher N50 value with a better assembled error corrected length read ensured more effectiveness of an algorithm. This result allowed for the first comparison between two prominent DNA algorithms, which hadn’t been compared before, to ensure better understanding Applications/Improvements: The applications of these results are endless, primarily, to ensure that work which involves assembled genome reads proceed with the utmost effectiveness. Any further improved algorithms, if created down the line, can aid in improving the entire process of the same. Thus, in the uniqueness of the results lies the novelty of the entire project.
De Novo assembly, De Bruijn graphs, ReadStack algorithm, Map Reduce, Hadoop, ALLPATHS-LG, CloudRS, VELVET, SSAKE, comparison.
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