Emily B. Sessa, Rishi R. Masalia, Nils Arrigo, Michael S. Barker, Jessie A. Pelosi
{"title":"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","authors":"Emily B. Sessa, Rishi R. Masalia, Nils Arrigo, Michael S. Barker, Jessie A. Pelosi","doi":"10.1002/aps3.11536","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Premise</h3>\n \n <p>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.</p>\n </section>\n \n <section>\n \n <h3> Methods and Results</h3>\n \n <p>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).</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>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.</p>\n </section>\n </div>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2023-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://bsapubs.onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.11536","citationCount":"1","resultStr":"{\"title\":\"GOgetter: A pipeline for summarizing and visualizing GO slim annotations for plant genetic data\",\"authors\":\"Emily B. Sessa, Rishi R. Masalia, Nils Arrigo, Michael S. Barker, Jessie A. Pelosi\",\"doi\":\"10.1002/aps3.11536\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Premise</h3>\\n \\n <p>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.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods and Results</h3>\\n \\n <p>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).</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusions</h3>\\n \\n <p>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.</p>\\n </section>\\n </div>\",\"PeriodicalId\":2,\"journal\":{\"name\":\"ACS Applied Bio Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2023-08-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://bsapubs.onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.11536\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Bio Materials\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/aps3.11536\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, BIOMATERIALS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"99","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/aps3.11536","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
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.