Significance analysis of microarrays (SAM) is a non-parametric, permutation-based method proposed specially for microarray data analysis (Tusher et al., 2001). It calculates the empirical False-Discovery Rate (FDR) by the random permutation of class labels. The permutation generates a null distribution, because the randomness is assumed to remove all biological effects. Therefore, it provides a means to control the false positives under various thresholds when multiple genes are assayed simultaneously in an array. The SAM package can handle both paired and non-paired data. It is run on top of the R statistical package, and has an excel interface using an excel plug-in.
|Project name||SAM service|
The data should be put in an Excel spreadsheet. The first row of the spreadsheet has information about the response measurement; all remaining rows have gene expression data, one row per gene.
The columns represent the different experimental samples.
Column 1 This should contain the gene name, for the user's reference.
For sequencing data, the values are counts and hence must be non-negative.
|Screening cycle||Decide according to your needs.|
|Deliverables||We provide you with raw data and analysis service.|
CD ComputaBio' SAM service can significantly reduce the cost and labor of the subsequent experiments. SAM Service is a personalized and customized innovative scientific research service. Each project needs to be evaluated before the corresponding analysis plan and price can be determined. If you want to know more about service prices or technical details, please feel free to contact us.