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Downstream analyses of short-reads from next-generation sequencing platforms are often preceded by a pre-processing step that removes uncalled and wrongly called bases. Standard approaches rely on their associated base quality scores to retain the read or a portion of it when the score is above a predefined threshold. It is difficult to differentiate sequencing error from biological variation without a reference using quality scores. The effects of quality score based trimming have not been systematically studied in  de novo  transcriptome assembly. Using RNA-Seq data produced from Illumina, we teased out the effects of quality score based filtering or trimming on  de novo  transcriptome reconstruction. We showed that assemblies produced from reads subjected to different quality score thresholds contain truncated and missing transfrags when compared to those from untrimmed reads. Our data supports the fact that  de novo  assembling of untrimmed data is challenging for de Bruijn graph assemblers. However, our results indicates that comparing the assemblies from untrimmed and trimmed read subsets can suggest appropriate filtering parameters and enable selection of the optimum  de novo  transcriptome assembly in non-model organisms.

A glance at quality score: implication for de novo transcriptome reconstruction of Illumina reads