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High throughput RNA sequencing (RNA-Seq) provides information on the location, structure and quantity of genes expressed. RNAseq data from eukaryotes or prokaryote can be mapped to a reference genome or used in de novo (without a reference) transcriptome assembly using assemblers such as transAbyss, Trinity and Velvet/Oases. RNASeq is also useful for the quantification of alternative splicing, detection of allelic variation and for the improvement of genome assembly. Most RNASeq data sets are used for differential expression analysis, a powerful tool that allows for the detection of expression levels among various conditions, cell types and developmental stages. Our bioinformaticists work with researchers to identify the appropriate amount of replication and sequencing depth to recover robust statistical information that supports the biological evidence on the difference in expression in genes of interest, or across the whole genome.