ARIBA: Antimicrobial Resistance Identification By Assembly
ARIBA is a tool that identifies antibiotic resistance genes by running local assemblies. It can also be used for MLST calling.
The input is a FASTA file of reference sequences (can be a mix of genes and noncoding sequences) and paired sequencing reads. ARIBA reports which of the reference sequences were found, plus detailed information on the quality of the assemblies and any variants between the sequencing reads and the reference sequences.
Please see the readme from the ARIBA github repository for installation instructions.
ariba getref card out.card
Prepare reference data for ARIBA
ariba prepareref -f out.card.fa -m out.card.tsv out.card.prepareref
Important: if the previous command reported warnings about removed sequences or variants, please take notice of them!
Inconsistent/bad data is removed and reported
in log files. If this happens, a warning will be written to
stderr. It is important to check any removed sequences and/or
variants. If you are missing a gene from your final output after running
ARIBA, please check that it was not removed by
Run local assemblies and call variants
ariba run out.card.prepareref reads1.fastq reads2.fastq out.run
Summarise data from several runs (in this case 3)
ariba summary out.summary out.run1/report1.tsv out.run2/report2.tsv out.run3/report3.tsv
View the results in
by dragging and dropping the files
out.summary.phandango.csv into the Phandago window.
The installation installs a single script called
ariba, which can be used to run
several tasks. Run
ariba with no options to list all the available tasks.
The tasks are:
- getref: Download reference data
- prepareref: Prepare reference data for running the pipeline
- refquery: Get cluster or sequence info from prepareref output
- run: Run the ARIBA local assembly pipeline
summary: Summarise multiple reports made by
- micplot: Plot MIC data
- expandflag: Expands flag column of report file
- flag: Translate the meaning of a flag output by the pipeline
- aln2meta: Make metadata input to preparef, using multialignment and SNPs
- test: Run on a small test dataset
- pubmlstspecies: Get available species from PubMLST
- pubmlstget: Download data for one species from PubMLST
- version: Print versions and exit