Expression Analysis shows sequencing of 10M fragments provides increased detection of content measured by microarray
Results from RNA-Seq experiments show a high correlation with those obtained from real-time PCR demonstrating the large dynamic range and extreme sensitivity of RNA-Seq.
RNA-Seq is able to detect and quantify more differential gene expression than arrays. For genes that have been detected as differentially expressed by both platforms, there is a high level of correlation. This enables researchers to leverage legacy data when transitioning from an array platform to next-generation sequencing.
Illumina sequencing workflow delivers full transcript sequence information in the minimal FASTQ format used by the 1000 Genomes Project. FASTQ files can be compressed to minimize storage and read directly by many popular aligners. After alignment, sequence output can be delivered in the familiar gene list format, common for microarray studies.
Several software packages are available that enable researchers to compare gene expression data from array and RNA-Seq experiments. These include Partek, a commonly used gene expression microarray analysis tool, which now offers the added functionality of processing and visualizing sequencing-based data. Sequencing data can be analyzed using heat maps and scatter plots to assess differential expression, much like arrays. Expression Analysis, an Illumina Commercial Service Provider, can deliver RNA-Seq results that are mapped to .CEL microarray formats for human, mouse, and rat, enabling direct comparison with microarrays. It has never been easier to compare RNA-seq to microarray data.