Team I Webserver Group

Members: Devishi Kesar, Shuheng Gan, Winnie Zheng, Priya Narayanan, Aaron Pfennig

Introduction

Objective

• Provide a comprehensive, automated platform to analyze E.coli isolates in order to predict virulence factors and outbreak cluster
• Functionalities of the webserver:
  • Identify virulence factors/microbial resistance and outbreak response for provided isolates
  • Allow data upload at each step of outline pipeline
  • Visualize findings in a comprehensible way
• Design
  • Intuitive usage
  • Provide only essential options

WebServer

• Structure
• Access to Webserver

Here is Link to access our webserver:

Functionalities

Genome Assembly

• Performs de-novo assembly with FastQ files as input
• Runs following tools by default:
  • fastp: read pre-processing
  • Unicycler: Genome assembly
• Options:
  • Perform read preprocessing
  • Kmer-size
  • Spades as alternative assembly method
• The input FastQ files must be paired-end reads
• Outputs as FASTA file
• Visualisation: Quast output

Gene Prediction

• Gene finding in assembled isolates or provided FASTA fileTakes FastQ files as input
• Runs following tools by default:
  • CDS: Prodigal
  • tRNA: Aragorn
  • rRNA: barrnap
• Options:
  • GeneMarkS-2 as alternative tool for CDS predictions
  • tRNAscan-SE as alternative tool for tRNA predictions
  • RNAmmer as alternative tool for rRNA predictions
• Outputs as *.gff file, *_cds.fna file, *_protein.faa file and *_rna.fna file

Functional Annotation

• Obtain functional information about predicted genes
• Input: FASTA file
• Cluster Tool: usearch
  • Output: centroid.fasta
• Homology Tools:
  • General annotation: InterProScan, EggNOGmapper
  • Antibiotic resistance gene: DeepARG
• Abinitio Tools:
  • Signal Peptides: SignalP 5.0
  • Transmembrane Proteins: TMHMM
  • CRISPR Sites: PilerCR
• Output: *.tsv file

Webserver Demo

• Choice One: Running General Pipline
• Choice Two: Running each step separately