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Medina, I; Tárraga, J; Martínez, H; Barrachina, S; Castillo, M I; Paschall, J; Salavert-Torres, J; Blanquer-Espert, I; Hernández-García, V; Quintana-Ortí, E S; Dopazo, J
DNA research, 04/2016, Letnik: 23, Številka: 2Journal Article
As sequencing technologies progress, the amount of data produced grows exponentially, shifting the bottleneck of discovery towards the data analysis phase. In particular, currently available mapping solutions for RNA-seq leave room for improvement in terms of sensitivity and performance, hindering an efficient analysis of transcriptomes by massive sequencing. Here, we present an innovative approach that combines re-engineering, optimization and parallelization. This solution results in a significant increase of mapping sensitivity over a wide range of read lengths and substantial shorter runtimes when compared with current RNA-seq mapping methods available.
