NSF Award
1553680
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.<br/><br/>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. <br/><br/>For further information see the project web site at: http://bioinformatics.astate.edu/assembly/
