FunctionAnnotator, a versatile and efficient web tool for non-model organism annotation

Ting Wen Chen, Ruei Chi Gan, Yi Kai Fang, Kun Yi Chien, Wei Chao Liao, Chia Chun Chen, Timothy H. Wu, Ian Yi Feng Chang, Chi Yang, Po Jung Huang, Yuan Ming Yeh, Cheng Hsun Chiu, Tzu Wen Huang, Petrus Tang*

*此作品的通信作者

研究成果: 期刊稿件文章同行評審

27 引文 斯高帕斯(Scopus)

摘要

Along with the constant improvement in high-throughput sequencing technology, an increasing number of transcriptome sequencing projects are carried out in organisms without decoded genome information and even on environmental biological samples. To study the biological functions of novel transcripts, the very first task is to identify their potential functions. We present a web-based annotation tool, FunctionAnnotator, which offers comprehensive annotations, including GO term assignment, enzyme annotation, domain/motif identification and predictions for subcellular localization. To accelerate the annotation process, we have optimized the computation processes and used parallel computing for all annotation steps. Moreover, FunctionAnnotator is designed to be versatile, and it generates a variety of useful outputs for facilitating other analyses. Here, we demonstrate how FunctionAnnotator can be helpful in annotating non-model organisms. We further illustrate that FunctionAnnotator can estimate the taxonomic composition of environmental samples and assist in the identification of novel proteins by combining RNA-Seq data with proteomics technology. In summary, FunctionAnnotator can efficiently annotate transcriptomes and greatly benefits studies focusing on non-model organisms or metatranscriptomes. FunctionAnnotator, a comprehensive annotation web-service tool, is freely available online at: http://fa.cgu.edu.tw/. This new web-based annotator will shed light on field studies involving organisms without a reference genome.

原文英語
文章編號10430
期刊Scientific Reports
7
發行號1
DOIs
出版狀態已出版 - 01 12 2017

文獻附註

Publisher Copyright:
© 2017 The Author(s).

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