- Installation
- Dependencies
- Aligners
- Download SUPER-FOCUS Database
- Running SUPER-FOCUS
- General Recomendations
- Ouput
- Citing
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
If you have Python 3.6, you can install both dependencies with:
pip install -r requirements.txt
One of the below aligners, which can easily be installed with conda
:
To install the aligners, having conda
installed, simply run:
conda install -c bioconda <aligner>
Note that they are all available from the bioconda
channel.
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.
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
- 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
SUPER-FOCUS output will be add the folder selected by the -dir
argument.
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:
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
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.