Team I Functional Annotation Group

Introduction

Background

Functional annotation is the process of locating genes and identifying their functions (biochemical functions, regulatory functions, etc.) in the genome.

Objective

• Fully annotate 258 genomes from Gene Prediction group, focusing on antibiotic resistance
• Provide Comparative Genomics group with data required to perform Genome Wide Association Study(GWAS)

Tools

Prokka

Command:

prokka --outdir <output_directory> --kingdom <species' kingdom> --genus <species' genus> --gram <> --prefix <output_file> --rfam --rnammer <input_file> 

• Runtime: ~ 16mins /genome

Eggnog

PilerCR

Command:

pilercr -in <input_file> -out <output_file>

• Runtime: <5 sec/genome

Phobius

Command:

phobius.pl -<output_format> <input_file> > <output_file>

• Runtime: 12-16mins /genome

LipoP

Command:

LipoP -<output_format> -<input_file> <output_file>

Runtime: ~2mins /genome

TMHMM

Command:

tmhmm -<output_format> -<input_file> <output_file>

• Runtime: ~6mins /genome

SignalP

Command:

signalp -t <organism_type> -f <output_format> <input_file>

• Runtime: ~ 4mins /genome

DeepARG DeepARG is a machine learning solution that uses deep learning to characterize and annotate antibiotic resistance genes in metagenomes. It contains two models for different inputs, short sequence reads and gene-like sequences Command:

• Runtime: 3min27s /genome

Interproscan

Command:

interproscan.sh -appl <application_you_want> -iprlookup -pa -i <input_file> -f <output_format> 

• -iprlookup: include lookup of corresponding InterPro annotation in the TSV and GFF3 format
• -pa: lookup of corresponding pathway annotation
• Runtime: 1min/genome, depends on applications you choose