Research Project 3
Algorithm development for splice alignment of long-read sequence data
About the Project
31.749,00 € (Gross)
- Integrate novel seeding technique (strobemers) to transcriptomic long-read alignment to genome.
- Adapt the exon-to-read chaining step in uLTRA of exons aligned to work without a reference annotation.
- Implement a post-alignment step that re-evaluates alignments based on reads aligned to the same region for alignment correction.
- Wobble Genomics (Richard Kuo): Evaluate uLTRA to improve TAMA collapse.
- CISC (Ana Conesa): Evaluate new mapper for quantification and integrate in SQANTI.
About the Main Supervisor and Host Group
I am an Assistant Professor at Stockholm University (the Department of Mathematics) and SciLifeLab Fellow at the national center for molecular biosciences, Science for Life Laboratory. I obtained my PhD in Computer science from KTH Royal institute of Technology and I have worked as a Postdoctoral researcher at Pennsylvania State University and at University of Helsinki. Before that I obtained a bachelor’s degree in mathematics and a master’s degree in mathematical statistics from Stockholm University, Sweden.
Our group develops computational methods to analyse large biological datasets. Particularly, we develop scalable algorithms for high-throughput genomic and transcriptomic sequencing data to study problems related to genome assembly, structural variation detection, and transcriptome analysis. We emphasise applicability of the methods and models to relevant biological and biomedical questions. For example, we have developed methods to cluster, error-correct and align long-transcriptomic reads (isONclust, isONcorrect, IsoCon, uLTRA), and indexing constructs for large scale sequence matching (strobemers), and algorithms for short-read alignment (strobealign). Detailed list can be found at our GitHub.