abhijeetsingh1704 / super-focus

A tool for agile functional analysis of shotgun metagenomic data

SUPER-FOCUS: A tool for agile functional analysis of metagenomic data

• Installation
• Dependencies
• Aligners
• Download SUPER-FOCUS Database
• Running SUPER-FOCUS
• General Recomendations
• Ouput
• Citing

Installation

This will give you command line program:

pip install superfocus

or

# clone super-focus
git clone https://github.com/metageni/SUPER-FOCUS.git

# install super-focus
cd SUPER-FOCUS && python setup.py install

# if you do not have super user privileges, you can install it like this
cd SUPER-FOCUS && python setup.py install --user

Dependencies

• Python >= 3.6
• Numpy 1.12.1
• SciPy 0.19.0

If you have Python 3.6, you can install both dependencies with:
pip install -r requirements.txt

Aligners

One of the below aligners, which can easily be installed with conda:

• DIAMOND 0.9.14
• RAPSearch2 2.24
• BLAST 2.6.0

To install the aligners, having conda installed, simply run:
conda install -c bioconda <aligner>

Note that they are all available from the bioconda channel.

Database

Use superfocus_downloadDB to download and format the SUPER-FOCUS database for the available aligners:

superfocus_downloadDB -a <aligner>

where <aligner> is rapsearch, diamond, or blast (or all of them separated by ,). You may choose as many aligners as you want among the three, as long as they are installed.

NOTE: RAPSearch2 and DIAMOND won't work properly if you are trying to use a database formatted with an incorrect version of the aligner. Thus, please re-run superfocus_downloadDB in case any aligner was updated on your system.

Run

The main SUPER-FOCUS program is superfocus. Here is a list of the available command line options:

-h print help

-q FASTA/FASTQ
	Path to directory with FASTA/FASTQ file(s)

-dir string
	output directory

-o string
	output prefix (default 'output_')

-mi float
	minimum identity (default 60 %)

-ml int
	minimum alignment (amino acids) (default: 15)

-focus int
	runs FOCUS; 1 does run; 0 does not run: default 0

-t int
	number of threads (default 4)

-e float
	e-value (default 0.00001)

-db string
	database (DB_90, DB_95, DB_98, or DB_100; default DB_90)

-p int
	amino acid input; 0 nucleotides; 1 amino acids (default 0)

-a string
	aligner choice (rapsearch (only fasta files) or diamond; default rapsearch)

-fast int
	runs RAPSearch2 or DIAMOND on fast mode - 0 (False) / 1 (True) (default: 1)

-n int
	normalizes each query counts based on number of hits; 0 doesn't normalize; 1 normalizes (default: 1)

Usage example: superfocus -q query.fasta -dir output_dir

Recomendations

• The FOCUS reduction is not necessary if not wanted (it is off by default: set -focus 1 to run FOCUS reduction)
• Run RAPSearch for short sequences, it is less sensitive for long sequences
• Primarily use DIAMOND for large datasets only. It is slower than blastx for small datasets
• BLAST is known for being really slow

Output

SUPER-FOCUS output will be add the folder selected by the -dir argument.

Citing

SUPER-FOCUS was written by Genivaldo G. Z. Silva. Feel free to create an issue or ask questions

If you use SUPER-FOCUS in your research, please cite:

Paper

Silva, G. G. Z., Green K., B. E. Dutilh, and R. A. Edwards:
SUPER-FOCUS: A tool for agile functional analysis of shotgun metagenomic data.
Bioinformatics. 2015 Oct 9. pii: btv584. Website: https://edwards.sdsu.edu/SUPERFOCUS

Extended tool manual

Silva, G. G. Z., F. A. Lopes, and R. A. Edwards
An Agile Functional Analysis of Metagenomic Data Using SUPER-FOCUS.
Protein Function Prediction: Methods and Protocols, 2017.