The information presented on this page will assist researchers in understanding what factors come to play in choosing a platform for gene expression, ChIP, DNA methylation status, miRNA, and SNP analysis. When selecting a platform there are a few important considerations including, the amount of starting material required (and whether or not amplification methods are available), which species are arrays available for, the number of probes on each array, and the cost of each.
If one of the primary goals for your proposed experiment is to be able to compare the data generated directly with data that has been generated from a previous experiment, then it will be necessary to use the same platform as in the original experiment.
All platforms (Illumina sequencing, Illumina arrays, Agilent arrays, Affymetrix arrays) generate high quality data.
However, not all platforms are equal in their tolerance of low quality or low quantity sample.
This is particularly true in the case of RNA and gene expression.
The Illumina array platform has a special component for dealing with either RNA, the DASL assay, or DNA, the Infinium FFPE DNA Restoration Solution, from FFPE samples.
When starting amount and quality are not limiting, the Illumina sequencing platform can provide the greatest amount of information; however, it also provides the greatest challenge for analysis (see the final question below).
Agilent and Affymetrix array platforms provide off-the-shelf solutions for the greatest variety of species.
Please refer to our Affymetrix array list or Agilent array list to determine if there is a solution for your species of interest.
Additionally, the Agilent platform also has the eArray tool, which can be used to create arrays from existing probe sets, or by uploading sequences.
Deep sequencing can be performed regardless of species; however, ease of analysis will be dependent on the level the genome is known to.
The number of samples that will be analyzed impacts the cost of the experiment, regardless of platform. However, in the case of Agilent or Illumina array platforms, there are multiple arrays multiplexed on one physical chip and all must be used together or they are wasted.
Maximizing the use of all arrays on each slide, for Agilent and Illumina, can greatly reduce the cost per sample.
It is a similar situation with deep sequencing, such that all lanes on a flow cell must be used at one time. The number of samples that can be analyzed with one lane on a flow cell varies depending on the depth of coverage required.
Depending on what type of experiment is being considered, a researcher's ability to analyze the data may factor into the decision process. With deep sequencing there is a large amount of data generated, and a complex pipeline may be needed to process the data into a form that can easily be understood. Before beginning any experiment, the analysis that will be needed must be assessed. Without properly considering the analysis requirements of a particular experiment, problems could arise that prevent full use of the data.