SAGPEK: fast and flexible approach to identify genotypes of Sanger sequencing data.

IF 3.3 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Jinpeng Wang, Shuo Sun, Yaran Zhang, Ning Huang, Chunhong Yang, Yaping Gao, Xiuge Wang, Zhihua Ju, Qiang Jiang, Yao Xiao, Xiaochao Wei, Wenhao Liu, Jinming Huang
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引用次数: 0

Abstract

Background: Although Sanger sequencing remains widely used in human genetic disease diagnosis and livestock breeding, software packages for analyzing such data have seen little innovation over time. Determining the genotypes of tens to hundreds of loci across hundreds or thousands of samples still typically relies on manual visual confirmation with traditional software, a process that is both time-consuming and prone to error.

Results: We present SAGPEK, a tool that automatically identifies genotypes at target loci from hundreds to thousands of ABI-format Sanger sequencing files and directly outputs the results. SAGPEK extracts the signal intensities for A, G, C, and T bases, performs base calling, and determines each site's homozygous or heterozygous status. It then generates a primary sequence composed of the bases with the highest signal intensities and records secondary bases for heterozygous sites. Using either built-in or user-provided anchor sequences, SAGPEK maps the coordinates of target loci, reports their genotypes, and, when applicable, annotates the corresponding amino acid changes.

Conclusions: SAGPEK provides an efficient, flexible, and user-friendly solution for analyzing ABI-format Sanger sequencing data, enabling simultaneous genotyping of tens of loci across hundreds of samples. Its innovation lies not in introducing new base-calling methods, but in integrating versatile functionalities-batch genotyping, customizable anchor sequences, amino acid alteration reporting, chromatogram visualization, and local execution-into a single open-source package. This makes SAGPEK well suited for applications such as human genetic disease screening, drug-resistance mutation detection, and functional mutation identification in livestock and other organisms.

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SAGPEK:快速和灵活的方法来确定基因型的Sanger测序数据。
背景:尽管Sanger测序仍然广泛应用于人类遗传疾病诊断和牲畜育种,但用于分析这些数据的软件包随着时间的推移几乎没有创新。在数百或数千个样本中确定数十到数百个基因座的基因型通常仍然依赖于传统软件的手动视觉确认,这一过程既耗时又容易出错。结果:我们提出了SAGPEK,这是一种工具,可以从数百到数千个abi格式的Sanger测序文件中自动识别目标位点的基因型,并直接输出结果。SAGPEK提取A、G、C和T碱基的信号强度,进行碱基调用,并确定每个位点的纯合或杂合状态。然后生成由信号强度最高的碱基组成的一级序列,并记录杂合位点的二级碱基。使用内置或用户提供的锚定序列,SAGPEK绘制目标位点的坐标,报告它们的基因型,并在适用时注释相应的氨基酸变化。结论:SAGPEK为分析abi格式的Sanger测序数据提供了一种高效、灵活和用户友好的解决方案,能够同时对数百个样本中的数十个基因座进行基因分型。它的创新不在于引入新的碱基调用方法,而在于将多种功能——批量基因分型、可定制的锚定序列、氨基酸变化报告、色谱可视化和本地执行——集成到一个单一的开源包中。这使得SAGPEK非常适合于人类遗传疾病筛选、耐药性突变检测以及牲畜和其他生物的功能突变鉴定等应用。
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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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