EasyDIVER + : An Advanced Tool for Analyzing High Throughput Sequencing Data from In Vitro Evolution of Nucleic Acids or Amino Acids.

IF 2.1 3区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Celia Blanco, Allison Tee, Pramesh Sharma, Matilda S Newton, Kun-Hwa Lee, Samuel E Erickson, Burckhard Seelig, Irene A Chen
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引用次数: 0

Abstract

In vitro evolution is a powerful technique for identifying functional nucleic acids and peptides, but the analysis of the resulting high-throughput sequencing data poses significant challenges, particularly in peptide selections. Existing bioinformatics tools often lack the specificity needed for this task, leaving researchers to navigate complex datasets with inadequate resources. To address these challenges, we present EasyDIVER + , an enhanced pipeline building on the foundation of the original EasyDIVER tool, which was designed for pre-processing sequencing data. EasyDIVER + not only processes raw, paired-end, demultiplexed Illumina read files but also introduces advanced analytical capabilities, including the calculation of enrichment values for each unique sequence across consecutive selection rounds. Furthermore, EasyDIVER + offers a highly flexible and customizable visualization platform, enabling detailed graphical representations of sequence metrics. These new features mark a significant advance in bioinformatics for peptide and protein data, providing researchers with intuitive tools for comprehensive data analysis and interpretation.

EasyDIVER +:用于分析核酸或氨基酸体外进化的高通量测序数据的先进工具。
体外进化是鉴定功能性核酸和多肽的一项强大技术,但分析由此产生的高通量测序数据带来了重大挑战,特别是在多肽选择方面。现有的生物信息学工具往往缺乏这项任务所需的特异性,使研究人员在资源不足的情况下浏览复杂的数据集。为了应对这些挑战,我们推出了EasyDIVER +,这是一种基于原始EasyDIVER工具的增强管道构建,专为预处理测序数据而设计。EasyDIVER +不仅处理原始的、对端、解多路的Illumina读取文件,还引入了先进的分析功能,包括在连续的选择轮中计算每个独特序列的富集值。此外,EasyDIVER +提供了一个高度灵活和可定制的可视化平台,可以实现序列指标的详细图形表示。这些新功能标志着肽和蛋白质数据生物信息学的重大进步,为研究人员提供了直观的工具进行全面的数据分析和解释。
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来源期刊
Journal of Molecular Evolution
Journal of Molecular Evolution 生物-进化生物学
CiteScore
5.50
自引率
2.60%
发文量
36
审稿时长
3 months
期刊介绍: Journal of Molecular Evolution covers experimental, computational, and theoretical work aimed at deciphering features of molecular evolution and the processes bearing on these features, from the initial formation of macromolecular systems through their evolution at the molecular level, the co-evolution of their functions in cellular and organismal systems, and their influence on organismal adaptation, speciation, and ecology. Topics addressed include the evolution of informational macromolecules and their relation to more complex levels of biological organization, including populations and taxa, as well as the molecular basis for the evolution of ecological interactions of species and the use of molecular data to infer fundamental processes in evolutionary ecology. This coverage accommodates such subfields as new genome sequences, comparative structural and functional genomics, population genetics, the molecular evolution of development, the evolution of gene regulation and gene interaction networks, and in vitro evolution of DNA and RNA, molecular evolutionary ecology, and the development of methods and theory that enable molecular evolutionary inference, including but not limited to, phylogenetic methods.
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