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)
Pipeline
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