Statistical refinement of primer design parameters
作者： Ellen M. Beasley , Richard M. Myers , David R. Cox , Laura C. Lazzeroni
DOI: 10.1016/B978-012372185-3/50006-7
关键词: Statistical model 、 Oligonucleotide 、 GC-content 、 Genome 、 Genetics 、 Exploratory data analysis 、 Template 、 Biology 、 Human genome 、 Computational biology 、 Primer (molecular biology)
摘要: Publisher Summary In the course of developing markers to build high-resolution radiation hybrid maps human genome, various primer pairs are developed for amplifying sequences from complex, mammalian, and whole genome DNA templates. The scale this development allows examining parameters used designing successful oligonucleotide polymerase chain reaction (PCR), using statistical modeling on large data sets. This chapter presents results such a analysis shows that modifying design significantly reduces marker failures. Here, three identified –length, GC content, and, specifically, content 3' half primer. By selection parameters, success gets highly improved. demonstrates potential exploratory optimize or other quantifiable PCR variables, maximize experimental success. While focus is primers designed development, should apply whenever high specificity priming with complex template required.
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