Efficient and Comprehensive Representation of Uniqueness for Next-Generation Sequencing by Minimum Unique Length Analyses

• DOI: 10.1371/journal.pone.0053822
• Publication Date: 2013-01-18T17:07:26Z
• Authors: Helena Storvall; Daniel Ramsköld; Rickard Sandberg
• Keywords: RNA-Seq; Representation; Identification; Tiling array

As next generation sequencing technologies are getting more efficient and less expensive, RNA-Seq is becoming a widely used technique for transcriptome studies. Computational analysis of data often starts with the mapping millions short reads back to genome or transcriptome, process in which some found map equally well multiple genomic locations (multimapping reads). We have developed Minimum Unique Length Tool (MULTo), framework comprehensive representation mappability information, through identification shortest possible length required each coordinate become unique transcriptome. Using minimum we compared different uniqueness compensation approaches transcript expression level quantification demonstrate that best achieved by discarding multimapping correctly adjusting gene model lengths. also explored within specific regions mouse enhancer experiments. Finally, making MULTo available community hope facilitate use eliminate need make additional files.