In the past few decades, the dangers of mycosis have caused widespread concern. With the development of the sequencing technology, the effective analysis of fungal sequencing data has become a hotspot. With the gradual increase of fungal sequencing data, there is now a lack of sufficient approaches for the identification and functional annotation of fungal chromosomal genomes. To overcome this challenge, this paper firstly deals with the approaches of the identification and annotation of fungal genomes based on short and long reads sequenced by using multiple platforms such as Illumina and Pacbio. Then this paper develops an automated bioinformatics pipeline called PFGI for the identification and annotation task. The experimental evaluation on a real-world dataset ENA (European Nucleotide Archive) shows that PFGI provides a user-friendly way to perform fungal identification and annotation based on the sequencing data analysis, and could provide accurate analyzing results, accurate to the species level (97% sequence identity).

在过去的几十年中，真菌病的危害引起了广泛关注。随着测序技术的发展，真菌测序数据的有效分析已成为热点。随着真菌测序数据的逐渐增加，现在缺乏用于鉴定和鉴定真菌染色体基因组的足够方法。为了克服这一挑战，本文首先探讨了通过使用多个平台（如Illumina和Pacbio）对短和长阅读序列进行测序的真菌基因组的鉴定和注释方法。然后，本文为识别和注释任务开发了称为PFGI的自动生物信息学管道。