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CD Genomics is committed to using microarray significance analysis methods to help customers screen for genes, proteins or metabolites that are significantly different from each other.

Introduction of SAM Service

Microarray gene chips use the integrated features of computer chips to lay thousands or tens of thousands of nucleic acid probes on special glass or silicon chips to form miniature detection devices. Microarray gene chips can help researchers to obtain massive amounts of gene expression data at the same time. How to integrate other biological information from the analysis and mining of gene expression data is a research idea to further discover the laws of biology.

Significance analysis of microarray is an algorithm for identifying differentially expressed genes on gene chips. In practice, in order to reduce the workload of subsequent work, the gene expression data preprocessing process wants to screen as many differentially expressed genes as possible, while ensuring a low number of false positives. Microarray significance analysis is an ideal tool for screening more characteristic genes with a lower false discovery rate.

SAM plotsheet outputs.Figure 1. SAM plotsheet outputs. (Roxas BA, et al., 2008)

Application Field

Significance analysis of microarray can be used for but not limited to the following research:

  • For gene expression profiling.
  • For miRNA analysis.
  • For comparative genomic analysis.
  • For DNA methylation analysis.
  • For custom single nucleotide polymorphism analysis.
  • For differential protein expression profiling.

CD Genomics SAM Service Pipeline

CD Genomics SAM Service Pipeline

SAM Service Content

  • We are able to link gene expression data to clinical feature data, find genes that correlate strongly with that feature, and then further analyze them in conjunction with other methods or data to reveal their intrinsic biological significance.
  • We are able to calculate observed scores and expected scores of proteins in different samples using SAM, and when the difference between t observed scores and expected scores of a protein in a sample exceeds a threshold, it proves that there is a significant difference in the expression of that protein.
  • We are able to use SAM service to help our customers identify the most important metabolites in metabolomics.

We are able to use SAM services to help our customers achieve high throughput data analysis in genomics, transcriptomics, proteomics, and metabolomics. For questions about analysis content, project cycle, and pricing, please click online inquiry.

How It Works

CD Genomics is a professional bioinformatics service provider with years of experience in NGS and long read sequencing (PacBio SMRT and Oxford Nanopore platforms) data analysis, integrated analysis services, database construction and other bioinformatics solutions.

How It Works

CD Genomics has professional bioinformatics experts who have successfully provided SAM services to researchers in many different fields. Our professional skills and enthusiasm will provide you with high-quality analysis services. If you are interested in our services, please contact us for more details.

Reference

  1. Bolón-Canedo V, et al. Challenges and Future Trends for Microarray Analysis. Methods Mol Biol. 2019; 1986: 283-293.
  2. Roxas BA, Li Q. Significance analysis of microarray for relative quantitation of LC/MS data in proteomics. BMC Bioinformatics. 2008 Apr 10; 9: 187.
* For Research Use Only. Not for use in diagnostic procedures.
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