48382 Summer studentship – Fast and accurate chromosome assembly – streamlining curation using image-based methods – Plant & Food Research

Description

Plant & Food Research (PFR) is a New Zealand science company delivering research and development designed to grow competitive advantage for clients in the horticulture, wine, cropping, seafood and associated high value food sectors worldwide.

Our summer studentship programme creates a special “career experience” for high calibre candidates. Our unique programme includes a full induction training day, a career planning session identifying potential pathways, a specific project – designed for you, as well as a final farewell and awards function.

This project aims to automate the final scaffolding process for genome assembly projects. High-quality and complete reference genome assemblies are fundamental for the application of genomics to biology, disease and biodiversity conservation. A genome assembly refers to the process of putting nucleotide sequences into the correct order and orientation. In order to achieve accurate assemblies at the chromosomal level from animal and plant genomes that are large and complicated, long-range linked data (i.e. Hi-C data) are required to accurately bridge assembly gaps (unassembled regions or missing regions due to lack of data) between contig-level sequences. We are using image-based method to post-scaffold genomic sequences onto chromosomal level based on Hi-C heatmaps. To contribute to this project, the student will mainly implement codes to generate appropriate images, test the existing image processing models on recognising features on the images and validate outcomes. The student will have the opportunity to develop computational and data science skills and contribute to the build of a tool for post-processing scaffolding of genome assemblies. The student will be mainly supervised by a bioinformatics scientist and a data scientist, but will also have the opportunity to work with the two teams.

Duties

You will need to implement python code to detect breaks/borders on the heatmaps generated from sequencing data using image-processing method, then reorder and reorientate sequences based on the detected breaks/borders for generating accurate genome scaffolds. You will need to clean and document your python codes on Github by the end of the studentship and report your progress within the team regularly.

Criteria for the Position

• Ideally you are a IT/Engineering student
• Experience in working on projects
• Excellent Python programming skill
• Experience in using Github
• Good interpersonal skills to work within a team

Ability to contribute to presentations and reports