Genome assembly composition of the String "ACGT" array: a review of data structure accuracy and performance...

Area of Science:

• Genomics and Bioinformatics
• Computational Biology
• Genome Assembly

Background:

• Advancements in sequencing technology generate massive genomic data, posing challenges for accurate genome assembly.
• Repetitive sequences (repeats) in genomes introduce ambiguity, leading to misassemblies and reduced accuracy in both de novo and reference-guided assembly approaches.
• Large read datasets create significant performance challenges for genome assembly algorithms.

Purpose of the Study:

• To provide an extensive review of genome assembly studies, focusing on accuracy and performance optimization.
• To highlight recent developments and limitations in handling repetitive sequences during genome assembly.
• To support researchers by consolidating information on genome assembly methodologies.

Main Methods:

• Review of existing literature on genome assembly, including de novo, reference-guided, and hybrid approaches.
• Analysis of repeat identification methods and their impact on assembly accuracy.
• Evaluation of performance optimization strategies such as data structure indexing and parallelization.

Main Results:

• Current repeat identification methods have limitations in detecting repeats of varying lengths and types, impacting assembly accuracy.
• Hybrid assembly approaches show promise but face challenges with repetitive sequences, increased computational cost, and time intensity.
• Parallelization in genome assembly, particularly for overlapping and read alignment, is not fully implemented in hybrid strategies.

Conclusions:

• Combining multiple repeat identification methods is recommended to improve repeat detection accuracy before hybrid assembly.
• Integrating genome indexing with parallelization is suggested for optimizing the performance of hybrid assembly approaches.
• Further research is needed to fully implement and optimize parallelization within hybrid genome assembly frameworks.