ena-STUDY-CME-28-10-2013-20:15:46:623-35
Our modified PANDAseq (Assembler) performs a modified statistical analysis using the sequencer supplied quality (Q) scores to find the most likely overlap, computes assembled Q scores for the read overlap region, and handles more complex overlap layouts
We have extended the existing PANDAseq paired-end reads assembly program. Our modified PANDAseq (Assembler) performs a modified statistical analysis using the sequencer supplied quality (Q) scores to find the most likely overlap, computes assembled Q scores for the read overlap region, and handles more complex overlap layouts .We have tested Assembler using two defined community samples from two different MiSeq runs against the paired-end assembler and quality filter built into Mothur (32), another amplicon analysis program. Assembler slightly outperformed Mothur on the high-quality dataset (Fig. 4A), and significantly outperformed on the average-quality dataset. In both datasets, Assembler outperformed the original PANDAseq when scored in a similar manner.
We have extended the existing PANDAseq paired-end reads assembly program. Our modified PANDAseq (Assembler) performs a modified statistical analysis using the sequencer supplied quality (Q) scores to find the most likely overlap, computes assembled Q scores for the read overlap region, and handles more complex overlap layouts .We have tested Assembler using two defined community samples from two different MiSeq runs against the paired-end assembler and quality filter built into Mothur (32), another amplicon analysis program. Assembler slightly outperformed Mothur on the high-quality dataset (Fig. 4A), and significantly outperformed on the average-quality dataset. In both datasets, Assembler outperformed the original PANDAseq when scored in a similar manner.