III: EAGER: Novel algorithms for de novo transcriptome assembly using RNA-seq data and for metagenome assembly

虽然高通量测序技术为揭示转录本或元基因组的复杂性提供了前所未有的机会，但它也给准确有效地将大量短片段组装成转录本或基因组带来了巨大的挑战。已经开发了许多汇编器，但它们都有限制其应用的局限性。该项目将开发新的方法，这将改变具有挑战性的转录组和元基因组组装的方法设计和开发。该项目还将通过研讨会和课程帮助教育学生如何有效地计算模型在应对生物信息学挑战方面发挥作用。基于最近发表在基因组生物学上的基于启发式方法的从头组装程序Bridger的初步工作获得的新见解，该项目将开发使用RNA-seq数据进行从头转录组组装的新算法。该方法的创新之处在于(1)不同于现有汇编程序的De Bruijn图或重叠图的新的图模型；(2)搜索算法，两者都将序列覆盖深度信息和成对端读取信息融入到程序中。预计与目前包括利邦在内的从头组装程序，甚至与袖扣或StringTie等当前基于参考的组装程序相比，新方法将实现显著提高的敏感性和特异性。此外，基于转录组组装的算法技术和转录组和元基因组组装的共同特征，本项目将探索和开发亚基因组组装算法，这是一项计算要求很高的任务，因为来自许多不同生物的大量短DNA序列片段的混合，以及不同生物测序覆盖的不一致。欲了解更多信息，请访问项目网站：http://bioinformatics.astate.edu/assembly/

While high-throughput sequencing technology provides an unprecedented opportunity to reveal the complexity of transcriptomes or metagenomes, it poses a significant challenge to accurately and efficiently assemble the huge amount of short fragments into transcriptomes or genomes. A number of assemblers have been developed, but they all have limitations that have hindered their applications. This project will develop novel approaches, which would transform the method design and development of the challenging transcriptome and metagenome assembly. This project will also help educate students through seminars and courses how effective computational models could make a difference in addressing bioinformatics challenges.Based on the new insights gained through the preliminary work on a heuristic approach-based de novo assembler Bridger, recently published in Genome Biology, this project will develop novel algorithms for de novo transcriptome assembly using RNA-seq data. The novelty of the approach lies in (1) new graph models, different from the de Bruijn graph or overlap graph of existing assemblers, and (2) the search algorithms, both of which will integrate sequence coverage depth information and paired-end reads into the procedure. It is anticipated that the new approach will achieve significantly increased sensitivity and specificity, compared with current de novo assemblers including Trinity or even current reference-based assemblers such as Cufflinks or StringTie. Furthermore, based on the algorithmic techniques developed for transcriptome assembly and the common features between transcriptome and metagenome assemblies, this project will explore and develop algorithms to assemble metagenomes, which is a computationally demanding task due to the mixture of large collections of short DNA sequence fragments from many different organisms, and the inconsistency of sequencing coverage of different organisms. For further information see the project web site at: http://bioinformatics.astate.edu/assembly/