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BAsic Rapid Ribosomal RNA Predictor
Barrnap predicts the location of ribosomal RNA genes in genomes.
It supports bacteria (5S,23S,16S), archaea (5S,5.8S,23S,16S),
metazoan mitochondria (12S,16S) and eukaryotes (5S,5.8S,28S,18S).
It takes FASTA DNA sequence as input, and write GFF3 as output.
It uses the new `nhmmer` tool that comes with HMMER 3.1 for HMM searching in RNA:DNA style.
Multithreading is supported and one can expect roughly linear speed-ups with more CPUs.
* [Perl 5.xx](https://dev.perl.org/perl5/) (core modules only)
* [nhmmer](https://hmmer.org/) (part of HMMER 3.x)
* [bedtools >= 2.27.0](http://bedtools.readthedocs.io/en/latest/)
Install [Conda](https://conda.io/docs/) or [Miniconda](https://conda.io/miniconda.html):
conda install -c bioconda -c conda-forge barrnap
Install [Homebrew](http://brew.sh/) (macOS) or [Linuxbrew](http://brew.sh/linuxbrew/) (Linux).
brew install brewsci/bio/barrnap
This will install the latest version direct from Github.
You'll need to add the `bin` directory to your `PATH`.
git clone https://github.com/tseemann/barrnap.git
% barrnap --quiet examples/small.fna
P.marinus barrnap:0.8 rRNA 353314 354793 0 + . Name=16S_rRNA;product=16S ribosomal RNA
P.marinus barrnap:0.8 rRNA 355464 358334 0 + . Name=23S_rRNA;product=23S ribosomal RNA
P.marinus barrnap:0.8 rRNA 358433 358536 7.5e-07 + . Name=5S_rRNA;product=5S ribosomal RNA
% barrnap -q -k mito examples/mitochondria.fna
AF346967.1 barrnap:0.8 rRNA 643 1610 . + . Name=12S_rRNA;product=12S ribosomal RNA
AF346967.1 barrnap:0.8 rRNA 1672 3228 . + . Name=16S_rRNA;product=16S ribosomal RNA
% barrnap -o rrna.fa < contigs.fa > rrna.gff
% head -n 3 rrna.fa
* `--help` show help and exit
* `--version` print version in form `barrnap X.Y` and exit
* `--citation` print a citation and exit
* `--kingdom` is the database to use: Bacteria:`bac`, Archaea:`arc`, Eukaryota:`euk`, Metazoan Mitochondria:`mito`
* `--threads` is how many CPUs to assign to `nhmmer` search
* `--evalue` is the cut-off for `nhmmer` reporting, before further scrutiny
* `--lencutoff` is the proportion of the full length that qualifies as `partial` match
* `--reject` will not include hits below this proportion of the expected length
* `--quiet` will not print any messages to `stderr`
* `--incseq` will include the full input sequences in the output GFF
* `--outseq` creates a FASTA file with the hit sequences
Barrnap does not do anything fancy. It has HMM models for each different rRNA gene.
They are built from full length seed alignments.
## Comparison with RNAmmer
Barrnap is designed to be a substitute for [RNAmmer](http://www.cbs.dtu.dk/services/RNAmmer/).
It was motivated by my desire to remove [Prokka's](https://github.com/tseemann/prokka)
dependency on RNAmmer which is encumbered by a free-for-academic sign-up
license, and by RNAmmer's dependence on legacy HMMER 2.x which conflicts
with HMMER 3.x that most people are using now.
RNAmmer is more sophisticated than Barrnap, and more accurate because it
uses HMMER 2.x in glocal alignment mode whereas NHMMER 3.x currently only
supports local alignment (Sean Eddy expected glocal to be supported in 2014,
but it still isn't available in 2018).
In practice, Barrnap will find all the typical rRNA genes in a few seconds
(in bacteria), but may get the end points out by a few bases and will
probably miss wierd rRNAs. The HMM models it uses are derived from Rfam,
Silva and RefSeq.
## Data sources for HMM models
12S RefSeq (MT-RNR1, s-rRNA, rns)
16S RefSeq (MT-RNR2, l-rRNA, rnl)
## Models I would like to add
Fungi [Sajeet Haridas]
LSU 35S ?
21S (multiple exons)
LSU ~2500bp 28S ?
SSU ~1500bp 16S ?
Plant [Shaun Jackman]
5S ~118 bp ? rrn5 (use RF00001 ?)
18S ~1935 bp ? rrn18 (use RF01960 ?)
26S ~2568 bp ? rrn26
## Where does the name come from?
The name Barrnap was originally derived from _Bacterial/Archaeal Ribosomal RNA Predictor_.
However it has since been extended to support mitochondrial and eukaryotic rRNAs, and has been
given the new backronym _BAsic Rapid Ribosomal RNA Predictor_.
The project was originally spawned at CodeFest 2013 in Berlin, Germany
by Torsten Seemann and Tim Booth.
* Barrnap: [GPLv3](https://raw.githubusercontent.com/tseemann/barrnap/master/LICENSE)
* Rfam: [CC0](https://raw.githubusercontent.com/tseemann/barrnap/master/LICENSE.Rfam)
* SILVA: [Free for academic use](https://raw.githubusercontent.com/tseemann/barrnap/master/LICENSE.SILVA)