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Description:
This script works like the identify_chimeric_seqs.py script, but is intended to make use of multicore/multiprocessor environments to perform analyses in parallel.
Usage: parallel_identify_chimeric_seqs.py [options]
Input Arguments:
Note
[REQUIRED]
[OPTIONAL]
Output:
The result of parallel_identify_chimeric_seqs.py is a text file that identifies which sequences are chimeric.
blast_fragments example:
For each sequence provided as input, the blast_fragments method splits the input sequence into n roughly-equal-sized, non-overlapping fragments, and assigns taxonomy to each fragment against a reference database. The BlastTaxonAssigner (implemented in assign_taxonomy.py) is used for this. The taxonomies of the fragments are compared with one another (at a default depth of 4), and if contradictory assignments are returned the sequence is identified as chimeric. For example, if an input sequence was split into 3 fragments, and the following taxon assignments were returned:
fragment1: | Archaea;Euryarchaeota;Methanobacteriales;Methanobacterium |
fragment2: | Archaea;Euryarchaeota;Halobacteriales;uncultured |
fragment3: | Archaea;Euryarchaeota;Methanobacteriales;Methanobacterium |
The sequence would be considered chimeric at a depth of 3 (Methanobacteriales vs. Halobacteriales), but non-chimeric at a depth of 2 (all Euryarchaeota).
blast_fragments begins with the assumption that a sequence is non-chimeric, and looks for evidence to the contrary. This is important when, for example, no taxonomy assignment can be made because no blast result is returned. If a sequence is split into three fragments, and only one returns a blast hit, that sequence would be considered non-chimeric. This is because there is no evidence (i.e., contradictory blast assignments) for the sequence being chimeric. This script can be run by the following command, where the resulting data is written to the directory “identify_chimeras/” and using default parameters (e.g. chimera detection method (“-m blast_fragments”), number of fragments (“-n 3”), taxonomy depth (“-d 4”) and maximum E-value (“-e 1e-30”)):
parallel_identify_chimeric_seqs.py -i repr_set_seqs.fasta -t taxonomy_assignment.txt -r ref_seq_set.fna -o chimeric_seqs.txt
ChimeraSlayer Example:
Identify chimeric sequences using the ChimeraSlayer algorithm against a user provided reference database. The input sequences need to be provided in aligned (Py)Nast format and the reference database needs to be provided as aligned FASTA (-a). Note that the reference database needs to be the same that was used to build the alignment of the input sequences!
parallel_identify_chimeric_seqs.py -m ChimeraSlayer -i repr_set_seqs_aligned.fasta -a ref_seq_set_aligned.fasta -o chimeric_seqs.txt