GOgetter:一个用于总结和可视化植物遗传数据GO精简注释的管道

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Emily B. Sessa, Rishi R. Masalia, Nils Arrigo, Michael S. Barker, Jessie A. Pelosi
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引用次数: 1

摘要

基因的功能注释是基因组分析的重要组成部分。总结功能注释的一种常用方法是使用分层基因本体,例如基因本体(GO)资源。GO包括有关细胞位置、分子功能以及基因产生或参与的产物/过程的信息。对于一组基因,为了描述数据集的整体功能,通常需要使用预定义的高阶项(GO slim)来总结GO注释,手动完成这一操作是不切实际的。方法和结果GOgetter管道由bash和Python脚本组成。从核苷酸基因序列的FASTA输入文件中,它输出文本和图像文件,其中列出(1)在一组参考基因模型中每个输入基因的最佳命中,(2)与这些命中相关的所有GO术语和注释,以及(3)数据集GO精简类别的摘要和可视化。根据下游需求,可以进一步查询这些输出文件并进行统计分析。结论GO注释是一种广泛使用的描述基因功能和产物的“通用语言”。GOgetter是一个快速且易于实现的管道,用于获取,汇总和可视化与一组基因相关的GO瘦类别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

GOgetter: A pipeline for summarizing and visualizing GO slim annotations for plant genetic data

GOgetter: A pipeline for summarizing and visualizing GO slim annotations for plant genetic data

Premise

The functional annotation of genes is a crucial component of genomic analyses. A common way to summarize functional annotations is with hierarchical gene ontologies, such as the Gene Ontology (GO) Resource. GO includes information about the cellular location, molecular function(s), and products/processes that genes produce or are involved in. For a set of genes, summarizing GO annotations using pre-defined, higher-order terms (GO slims) is often desirable in order to characterize the overall function of the data set, and it is impractical to do this manually.

Methods and Results

The GOgetter pipeline consists of bash and Python scripts. From an input FASTA file of nucleotide gene sequences, it outputs text and image files that list (1) the best hit for each input gene in a set of reference gene models, (2) all GO terms and annotations associated with those hits, and (3) a summary and visualization of GO slim categories for the data set. These output files can be queried further and analyzed statistically, depending on the downstream need(s).

Conclusions

GO annotations are a widely used “universal language” for describing gene functions and products. GOgetter is a fast and easy-to-implement pipeline for obtaining, summarizing, and visualizing GO slim categories associated with a set of genes.

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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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