Generate consensus-based taxonomic assignments from BLAST results.
Please cite the following paper when using BROCC:
Dollive S, Peterfreund GL, Sherrill-Mix S, Bittinger K, Sinha R, Hoffmann C, Nabel CS, Hill DA, Artis D, Bachman MA, Custers-Allen R, Grunberg S, Wu GD, Lewis JD, Bushman FD. A tool kit for quantifying eukaryotic rRNA gene sequences from human microbiome samples. Genome Biol. 2012 Jul 3;13(7):R60. doi: 10.1186/gb-2012-13-7-r60.
To install BROCC, run this command in the current directory.
pip install .BROCC has two methods of looking up taxon names: it can use a local copy of the NCBI taxonomy, or it can use NCBI's E-utilities to ask for names over the web. Using a local copy of the NCBI taxonomy is much faster and more reliable. To prepare this taxonomy database, use the command:
create_local_taxonomy_db.pyYou will need about 5G for the taxonomy databaase, which is stored at
~/.brocc/taxonomy.db by default.
The BROCC classifier takes BLAST results as input, using output format 7 (see BLAST documentation). The following BLAST parameters are found to work best for amplicon-based sequence sets:
blastn -query <SEQUENCES (FASTA FORMAT)> -evalue 1e-5 -outfmt 7 -db nt -out <BLAST RESULTS> -num_threads 8 -max_target_seqs 100The BROCC program requires two input files and the name of an output directory:
brocc.py -i <SEQUENCES (FASTA FORMAT)> -b <BLAST RESULTS> -o <OUTPUT DIRECTORY>brocc.py outputs a QIIME-formated taxonomy map and a couple of log
files, giving details on the voting.
The BROCC command has several options for consensus formation:
The defaults are currently set for the ITS1 gene, because these settings seem to work well over several different amplicons. The minimum identity defaults for ITS1 are 95.2% at the species level and 83.05% at the genus level (taken from Liggenstoffer et al). For 18S, settings of 99.0% at the species level and 96.0% at the genus level seem to produce the most accurate and stable assignments.