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- W2028851248 abstract "The selection of an appropriate assembler is important to obtain best assembly of a fragment dataset, avoid misassembles and minimize further finishing effort. It is known that the assembly quality of assemblers is dependent on the input data parameters such as DNA fragmentation parameters and genome sequence structure. To the best of our knowledge no large scale systematic effort has been made in quantifying the quality of the assembly generated by various assemblers over a range of input parameters. The correlation between input parameters and assembler quality can be used to define the characteristics of an assembler and design an optimal assembler selection algorithm. The critical barrier is the computational challenge of assembling simulated high-throughput sequence libraries of thousands of genomes with input parameters varied to cover the spectrum of values obtained from major sequencers available to biologists today. We present a study to show that a quantifiable correlation can be drawn between their input and output characteristics for four major open-source assemblers. Based on our result we propose a simple model to estimate the quality of assemblies generated by these assemblers for given input parameters." @default.
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- W2028851248 date "2014-09-20" @default.
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- W2028851248 title "Big data challenges for estimating genome assembler quality" @default.
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