Microarrays are widely used to evaluate gene expression at the genome scale. However, all too often the importance of data analysis at the level of the individual probe is overlooked. This is a particular problem when trying to detect differences in gene expression levels among genetically unique animals, across inbred animal strains, or among genetically modified animals. Of particular concern is the presence of small modifications in the DNA (i.e., single nucleotide polymorphisms [SNPs]) that occur naturally and differentiate one individual from the next. This article describes the potential impact of SNPs on analyses of gene expression differences and introduces an approach called SNP masking, which implements removal of SNP-affected probes. SNP masking is a valuable and feasible approach that can ameliorate these hybridization problems.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3860483 | PMC |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!