RSCUcaller: an R package for analyzing differences in relative synonymous codon usage (RSCU).

IF 3.3 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Mateusz Maździarz, Sebastian Zając, Łukasz Paukszto, Jakub Sawicki
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引用次数: 0

Abstract

Background: Synonymous codon usage bias, a significant factor in gene expression and genome evolution, was extensively studied in genomics and molecular biology. Although the genetic code is universal, significant variations in synonymous codon usage have been observed among and within organisms. This bias was linked to various factors, including gene expression levels, tRNA abundance, protein structure, and environmental adaptation. Relative Synonymous Codon Usage (RSCU), a normalized measure, was used to quantify this bias. By analyzing RSCU values, researchers uncovered patterns and trends related to the underlying mechanisms driving codon usage bias.

Results: We present an R package named RSCUcaller designed for the analysis of coding nucleotide sequences at the level of relative synonymous codon usage (RSCU). The package enables both visualization of data and the performance of advanced statistical analyses. RSCUcaller accepts as input a multi-fasta file containing coding sequences (CDS) and an accompanying description table. Alternatively, the user may provide separate fasta files for each sequence along with the corresponding table. The program merges the provided sequences and calculates RSCU values for each. Implemented visualization features include creating heatmaps and dendrograms based on these heatmaps. Furthermore, the package allows for the presentation of data in the form of histograms. The calculated RSCU values can also be used to create matrices that can be subjected to further analysis by the user. RSCUcaller offers the functionality of correlation analysis between any two organisms. Additionally, to compare the frequency of amino acid occurrence between different groups of sequences, statistical tests have been implemented.

Conclusions: RSCUcaller enabled comparative RSCU analysis between coding sequences of different organisms or individuals of the same species. It facilitated visualization and statistical analysis among codons and user-defined groups. The RSCUcaller package is available at https://github.com/Mordziarz/RSCUcaller under the GPL-3 license.

RSCUcaller:一个用于分析相对同义密码子使用差异的R包。
背景:同义密码子使用偏差是影响基因表达和基因组进化的重要因素,在基因组学和分子生物学中得到了广泛的研究。虽然遗传密码是普遍的,在同义密码子的使用显著差异已被观察到在生物之间和内部。这种偏差与多种因素有关,包括基因表达水平、tRNA丰度、蛋白质结构和环境适应。相对同义密码子使用(RSCU)是一种标准化的测量方法,用于量化这种偏差。通过分析RSCU值,研究人员揭示了驱动密码子使用偏好的潜在机制的模式和趋势。结果:我们提出了一个名为RSCUcaller的R包,用于在相对同义密码子使用(RSCU)水平上分析编码核苷酸序列。该软件包支持数据可视化和高级统计分析的性能。RSCUcaller接受包含编码序列(CDS)和附带的描述表的多fasta文件作为输入。或者,用户可以为每个序列提供单独的fasta文件以及相应的表。该程序合并提供的序列并计算每个序列的RSCU值。实现的可视化功能包括基于这些热图创建热图和树形图。此外,该包允许以直方图的形式表示数据。计算出的RSCU值还可以用于创建矩阵,用户可以对其进行进一步分析。RSCUcaller提供了任何两个生物体之间的相关性分析功能。此外,为了比较不同组序列之间氨基酸出现的频率,已经实施了统计检验。结论:RSCUcaller实现了不同生物或同一物种个体之间编码序列的比较RSCU分析。它促进了密码子和用户定义组之间的可视化和统计分析。RSCUcaller包在GPL-3许可下可在https://github.com/Mordziarz/RSCUcaller获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
BMC Bioinformatics
BMC Bioinformatics 生物-生化研究方法
CiteScore
5.70
自引率
3.30%
发文量
506
审稿时长
4.3 months
期刊介绍: BMC Bioinformatics is an open access, peer-reviewed journal that considers articles on all aspects of the development, testing and novel application of computational and statistical methods for the modeling and analysis of all kinds of biological data, as well as other areas of computational biology. BMC Bioinformatics is part of the BMC series which publishes subject-specific journals focused on the needs of individual research communities across all areas of biology and medicine. We offer an efficient, fair and friendly peer review service, and are committed to publishing all sound science, provided that there is some advance in knowledge presented by the work.
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