This paper reports on a project that sought to optimize the filter metrics for sequence quality assessment, noting before- and after-optimization metrics.
Filter metrics are used as a quick assessment of sequence trace files in order to sort data into different categories (i.e. high quality, review, and low quality) without human intervention. The filter metrics consist of two numerical parameters for sequence quality assessment: trace score (TS) and contiguous read length (CRL). Primer-specific settings for the TS and CRL were established using a calibration dataset of 2817 traces and validated using a concordance dataset of 5617 traces. Prior to optimization, 57 percent of the traces required manual review before import into a sequence analysis program, whereas after optimization only 28 percent of the traces required manual review. After optimization of primer-specific filter metrics for mitochondrial DNA sequence data, an overall reduction of review of trace files translates into increased throughput of data analysis and decreased time required for manual review. (Published Abstract Provided)