PhD Opportunity: Kmer Graph Representation of Pangenomes for Rapid Pathogen Genomic Sequence Analysis at University of Birm

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PhD Opportunity: Kmer Graph Representation of Pangenomes for Rapid Pathogen Genomic Sequence Analysis
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- Institute of Microbiology and Infection
Qualification Type:
PhD
Location:
Birmingham
Funding for:
UK Students
Funding amount:
The position offered is for three and a half years full-time study. The value of the award is stipend; £15,609 pa; tuition fee: £4,500. Awards are usually incremented on 1 October each year.
Hours:
Full Time
Placed On:
2nd March 2022
Closes:
31st March 2022
In order to better guard against the rapid spread of high-risk strains of infectious diseases in the future, we must better leverage the large scale collection and processing of genomic data that is possible with today’s technologies. A key example of this is the data that will soon be produced by the Nucleic Acid Observatory. This initiative aims to set up continuous spatiotemporal monitoring of kmers in the environment, communities, and wastewater using metagenomic sequencing. The number of kmers generated in this initiative is likely to reach a scale never before processed and there is a need to think of innovative ways to process the data quickly and store it efficiently.
The current approach to dealing with genomic data flexibly is to convert it into kmers - words of a fixed length. The presence and absence of these words can be used to represent the genetic diversity contained in an environment, patient sample, or population of a given pathogen. However, breaking genomic data into kmers can create a very large dataset on the order of 10-100 million kmers/variables representing thousands of samples.
One way of reducing this data is to collapse overlapping kmers that are found in the same samples into larger units called unitigs. This can be done using de Bruijn graphs (DBGs), which are normally used for assembling genomes. This can drastically reduce the number of variables to consider in an analysis without any loss of information. For some applications, however, even this may produce too much data. Minimizer-space de Bruijn graphs (MDGBs) are an exciting new development that may provide more drastic reductions in dataset size. In MDBGs, DNA sequences are reduced to an ordered set of subsequences that only represent a subset of the total sequence. The benefit of this reduced representation is a massive speedup in analysis time and reduced storage footprint. However, with this compression of complex biological information, there is a risk we may lose vital signal that we need for a meaningful analysis of the data.
This project aims to address several key questions:
How much overlap is there in individual kmers from longitudinal metagenomic sequencing?
How much overlap is there in regions of a pangenome graph from longitudinal metagenomic sequencing?
Can we speed up monitoring of genomic diversity in metagenomics experiments through the use of MDGBs? Does this result in a loss of sensitivity or specificity when monitoring for species of interest?
Applicants should have a background in bioinformatics, biology, biochemistry, physics, mathematics, computer science, or a related subject. The project will involve computational analysis of DNA sequence data and require programming skills. Prior proficiency in Python is preferred. Preference will be given to applicants with prior experience analyzing microbial genomic data or working with kmer and/or graph structured data. We want our PhD student cohorts to reflect our diverse society. UoB is therefore committed to widening the diversity of our PhD student cohorts. UoB studentships are open to all and we particularly welcome applications from under-represented groups, including, but not limited to BAME, disabled and neuro-diverse candidates. We also welcome applications for part-time study.
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