Optimizing the RNA-Seq transcriptome discovery pipeline for Aspergillus fumigatus.

Suman Pakala, Vinita Joardar, Nikhat Zafar, Suchitra Pakala, Sean Murphy, Natalie Fedorova and William Nierman J.

Author address: 

Craig Venter Institute, Rockville, MD, USA.


RNA-Seq has become invaluable to applications such as transcript expression quantification and genome annotation, including discovery of non-coding RNAs and identification of new gene models and isoforms. The continued evolution of deep sequencing technologies has resulted in active development of new data analysis tools. It has become necessary for research groups to identify the appropriate set of tools that best suit their needs. As part of the Aspergillus fumigatus re-annotation project, we sequenced several cDNA libraries using Illumina GA II and evaluated publicly available transcript discovery approaches. Specifically, this comparison includes (i) the de novo transcript assembly approach, (ii) the alignment followed by assembly of transcripts approach and also (iii) a hybrid approach for transcript identification. Performance of various short read aligners, splice junction mappers, and transcript assemblers that implement these approaches have been evaluated. Based on this study, we present a general framework for evaluating RNA-Seq data analysis tools and discuss our results of such an evaluation and optimization of the analysis pipeline for the A. fumigatus genome.

abstract No: 


Full conference title: 

26th Fungal Genetics Conference
    • Fungal Genetics Conference 26th (2005)