Microarrays and RNA Sequencing Education
I use microarrays
Microarrays have historically been used for RNA profiling; however, this technique suffers from significant shortcomings, such as low specificity, sensitivity, and dynamic range, which reduce accuracy.
It has become increasingly evident that transcription in human cells is an intricate and dynamic process. Transcriptome sequencing, often referred to as RNA-Seq or RNA sequencing, provides the most complete method of analyzing the transcriptional content of cells.
Advance your gene expression research with RNA-Seq
RNA sequencing using Ion Torrent™ next-generation sequencing (NGS) is a higher sensitivity, affordable, and simple alternative to gene expression analysis using microarrays. With increased sensitivity and the ability for both discovery and routine gene expression assays, NGS expands your research capabilities. RNA-Seq provides a wider dynamic range and greater sensitivity allowing you to use less starting material and see low-level expression changes that may have been missed with microarrays.
What microarray applications should I consider for NGS?
RNA sequencing provides hypothesis-free whole-transcriptome analysis. It is ideal for standard differential gene expression research studies and also allows you to identify all genomic regions that are transcribed, find gene fusions, and discover splice variants, novel isoforms, and noncanonical transcripts—providing much more information than microarray analysis.
Transitioning from microarrays to RNA (transcriptome) sequencing can lead to new discoveries and provide more sensitive results while maintaining good correlation to previous microarray studies. Transcriptome sequencing data are highly correlated with microarray and qPCR data for identified differentially expressed genes. For more information, view the transcriptome sequencing application note.
Getting started with transcriptome sequencing
Visit our Getting Started with Ion Torrent™ Transcriptome Sequencing resource to learn more about RNA sequencing, attend a webinar, and view a case study for biomarker discovery using RNA sequencing.