Daniel Mendoza

Helios Scholar

Quality trimming of genomic sequences plays an important role in bioinformatics data analysis. This process involves the removal of adapters and  condensing of genomic sequence  based on the quality of the Phred scores. ezTrim was developed using C++ in attempt to create a faster quality trimming tool and is designed to process data by using pattern searching algorithms and parallel processing. InitiallyezTrim utilizes the Boyer Moore algorithm for adapter removal followed by the Sliding Window algorithm for quality trimming. In comparison to industry standard alternatives, ezTrim had a runtime of 24:52 min while fastp was able to perform in  13:38 min, Cutadapt had the slowest time of 30:33 min and seqtk was the fastest, but lacked some capabilities other tools have. Having efficient bioinformatic tools is crucial, where time saved can have a substantial impact on overall pipeline efficiency. Future work aims to extend the capabilities of ezTrim to include paired-end functionality while further optimizing its speed. By incorporating these enhancements, ezTrim has the potential to become a beneficial tool for computational biology.