Group all dicty genes into functional groups and compute respective codon usages.
The program is started by calling python main.py. Blast-specific applications can be executed via python scripts/blaster.py.
Setup a local blast instance by running ./blast_setup.sh. Before initializing the local database, download the list of taxids-to-be-extracted via python taxid_crawler.py. Then simply execute ./blast_db_setup.sh (this might take a while and requires loads of RAM).
Classifiers need to have a static variable data_file specifying the fasta file they are going to act on. They may furthermore have a static preprocessing(genes) function which acts on the given list of biopython's SeqRecord entries.
Their most important part is the get_groupname(self, record) method, which assigns a record to its logical group (as this function returns a list, it is possible to assign one entry to multiple groups). This group is then used in all later processing steps.
All filters reside in filters.py. Each filter must have an apply(self, record) method, which takes one record (biopython's SeqRecord) as its argument.
This method returns True if the respective record should be kept and False otherwise.
A filter may have the static variable post_annotation (defaults to False), which declares that this filter should be applied after gene annotations took place.
Dicty's primary CDS was acquired from dictybase. The gene annotations were retrieved using AmiGO 2.
The external (non-standard) python modules used in this project are: