Team II Webserver Group
Introduction
Background
A web server is a server that hosts web pages as requested. It takes in requests in the form of HTTP(Hyper Text Transfer Protocol) and then stores, processes data at the same time. Here, we build a web server that ideally predicts a phenotype based on the genetic information it is given.
Goal
The web server should provide the following:
1. An easy-to-use tool to help distinguish between Klebsiella phenotypes, by implementing the work of the comparative genomics group.
2. A robust and easy-to-use web-based de-novo assembly tool.
3. A feature to visualize and download the results of the 258 genomes.
Design Principles
1. Minimal
2. Mobile Friendly
3. Short Load Time
4. Contrasting Colors
Functionalities Offered
Genome Assembly
Users will have the option of uploading either an assembled genome or short-reads from NGS methods. If short-reads are provided, a de novo assembly will be performed using the assembler Skesa. The resulting assembly will be available for download and will be used for downstream processes.
Strain and Species Identification
Strain identification is performed using k-mer based approaches in StrainSeeker. Each user-provided input sample is reduced to a pool of unique k-mers that is compared to k-mer pools from samples in the NCBI sequence database. The observed and expected k-mer pool overlaps between user-provided samples and NCBI-samples are used to taxonomically place samples with unknown strain identity.
Antibiotic-resistance Profiling
Each user-provided sample will be compared to the Comprehensive Antibiotic Resistance Database (CARD) using the toolkit RGI. RGI discovers high-confidence homologues of known antibiotic-resistance genes using Diamond homology searches. RGI also incorporates SNP models to predict genetic variants that are likely to confer new antibiotic resistances. The entire antibiotic profile of each strain is visualized in a wheel-chart (provided by RGI) that allows the user to explore result by drug class, mechanism of resistance, and antibiotic target.
Virulence Factor Profiling
Each user-provided sample will be blasted against the Virulence Factor Database (VFDB) to identify homologues of known virulence factors. A non-redundant blast output (outfmt 6) will be provided for download by the user.
Tools
Skesa
Skesa is the most recent tool in our list and is currently used by NCBI. Information about the algorithm is currently unavailable. . De novo sequencing refers to sequencing a novel genome where there is no reference sequence available for alignment. Sequence reads are assembled as contigs, and the coverage quality of de novo sequence data depends on the size and continuity of the contigs (ie, the number of gaps in the data).
To compare the performance of the above tools, we use Quast.
StrainSeeker
StrainSeeker is a program for detecting bacterial strains from raw sequencing reads. Compared to other similar programs, it offers the following advantages:
1. Fully customizable database - use your own strains of interest or download our database
2. Detect novel strains that are related to strains in the database
3. Quickly handle large amounts of data
4. Results given all the way down to the strain level!
Input
Fastq or Fasta sample
Output tree
RGI
VFDB
The virulence factor database (VFDB) is dedicated to providing up-to-date knowledge of virulence factors (VFs) of various bacterial pathogens.
1. Blastn against VFDB
2. Remove redundant matches, output list of unique VF homologues -Accession numbers, blast scores, positions in query
Our Web Page
Home Page
Basic Layout
Assembly Page
Batch mode