Team I Webserver Group
Web Server
Team
Dongjo Ban, Genevieve Brandt, Yuntian He, Ryan Place, Nirav Shah, Casey Smith, Mohit Thakur, Stephen Wist
Introduction
Background
The goal of our predictive webserver is to process biological data and output the results of the analysis in a user-friendly format. We will provide information about an input sample's antibiotic resistance and other biological traits such as genus, species, and strain.
Goals
- Assemble input reads
- Analyze assemblies
- Visualize results
- Implement a way for results to be downloaded
Technologies Used
PHP was used because it is a universal web language that has numerous useful libraries and is easy to integrate with HTML. This was used with Laravel to allow for rapid application development.
Functionalities
De Novo Genome Assembly
FastQC was used to perform quality control checks on the raw input sequence data. Then, de novo sequencing was used in our pipeline because no reference sequence is needed in this case. Sequence reads are assembled as contigs, and the coverage quality of de novo sequence data depends on the size and continuity of the contigs. We used Skesa for de novo genome assembly. This tool is currently unpublished.
Species & Strain Typing
Genome Database
We created a curated list of genes that are included in the 258 Klebsiella genomes we were given, performed a literature review to find genes that may indicate colistin resistance, and built a gene panel to help us find phenotypic indicators in our assembled genomes. We will be using a MySQL database that will show 0 (absent) or 1 (present) for both antibiotic resistance genes and virulence factor genes.