Evaluating assembly pipeline for transcriptomes

The gene expression and transcriptome analysis are currently some of the main focuses of research for great number of biologists. The assembly of raw sequence data to obtain a draft transcriptome is a multi-stage pipeline consisting of complex steps like data cleaning, contaminant removal, error correction, de novo assembly, redundancy removal, and assembly validation. In this paper we developed and tested five transcriptome assembly pipelines for wheat transcriptome by using different tools. The assemblers Velvet- Oases and Trinity which use multiple and single k- mer methods respectively are used for our pipeline. In addition to that, different tools are used in the process of data cleaning and redundancy removal. The analysis of the results obtained from the five different assemblies show that the transcripts generated from Velvet-Oases with multiple k-mev approach and Oases-M have higher alignment ratio with the reference TriFLDB wheat transcriptome dataset.