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The assembly evaluation process is the starting step towards meaningful downstream data analysis. We need to
know how much accurate information is included in an assembled sequence before going further to any data analysis
stage. Four basic metrics are targeted by different assembly evaluation tools: contiguity, accuracy, completeness, and
contamination. Some tools evaluate these metrics based on comparing the assembly results to a closely related reference.
Others utilize different types of heuristics to overcome the missing of a guiding reference, such as the consistency
between assembly results and sequencing reads. In this paper, we discuss the assembly evaluation process as a core stage
in any sequence assembly pipeline and present a roadmap that is followed by most assembly evaluation tools to assess
different metrics. We highlight the challenges that currently exist in the assembly evaluation tools and summarize their
technical and practical details to help the end-users choose the best tool according to their working scenarios. To address
the similarities/differences among different assembly assessment tools, including their evaluation approaches, metrics,
comprehensive nature, limitations, usability and how the evaluated results are presented to the end-user, we provide a
practical example for evaluating Velvet assembly results for S. aureus dataset from GAGE competition. A Github
repository (https://github.com/SaraEl-Metwally/Assembly-Evaluation-Tools) is created for evaluation result details along
with their generated command line parameters.
Whole-genome shotgun sequence assembly enables rapid gene characterization in the tropical fish barramundi,Lates calcarifer
