PARSID: a Python script for automatic analysis of local BLAST results for a rapid molecular taxonomic identification

Objective: A reliable taxonomic identification of species from molecular samples is the first step for many studies. For researchers unfamiliar with programming, running a BLAST analysis, filtering, and organizing results for hundreds of sequences through the BLAST web interface can be difficult. Additionally, sequences deposited in GenBank can have outdated taxonomic identification. The use of reliable Reference Sequences Library (RSL) containing accurate taxonomically-identified sequences facilitates this task. Pending the availability of a RSL with the user, we developed a tool that automates the molecular taxonomic identification of sequences. Results: We developed PARSID, a Python script running through the command-line that automates the routine workflow of blasting an input sequence file against the user’s RSL, and retrieves the matches with the highest percentage of identity in five steps. PARSID accepts cut-off parameters and supplementary information in a.csv file for filtering the results. The final output is visualized in a spreadsheet. We tested its functioning using 10 input sequences simulating different situations of the molecular taxonomic identification of sequences against an example RSL containing 25 sequences. Step-by-step instructions and test files are publicly available at https://github.com/kokinide/PARSID.git .