My review of the book (on Amazon):
This book gives an interesting overview of the field of next-generation sequencing and its implications for personal genomics. Kevin Davies provides a snapshot of the technology in the next-generation sequencing companies, in particular explaining how 454 capitalized on emulsion PCR, how Solexa contributed reversible terminator chemistry and cluster PCR, how Ion Torrent utilized the principles of a pH meter for sequencing, &c. He also gives a quick overview of all the personal genomics companies giving one a sense of their unique angle - i.e. deCODEme with its strong science capitalizing on the unique genetics of Iceland, Navigenics with its more medically oriented and paternalistic style and 23andme with its more social networking angle.
Davies also talks a little bit about how we should appreciate the results from personal genomics companies and how currently, except for the APOE gene, most of the results that we get would have very low odds ratios and effect sizes and are more of a curiosity -- but the whole enterprise has strong ethical implications.
Some other quick points that I thought interesting in the book :
• The relative risk of 1.6 for high cholesterol (top 20%) is a useful measuring stick for gene effects. Now in comparison, from the 23andme site, "Studies have shown that the odds of developing AD increases with each copy of the ε4 variant of APOE. One copy is associated with about two times increased odds of developing AD and two copies is associated with about 11 times increased odds in populations of European ancestry, compared to average." (https://www.23andme.com/health/alzheimers/techreport)
* The books starts with many personal stories (Watson, Rothberg, Gibbs, etc). It portrays Decode’s Jeff Gulcher’s finding that he had prostate cancer as a triumph of genomics that saved him. It mentions that Watson didn't want to know his APOE genotype but it was cracked using LD.
* The book discusses how the many personal genomics companies differ in the risk they report. This could be due to genotyping errors but more probably it has to do with the different panels of diagnostic SNPs that they include in their models for relative risk of various diseases. It also
shows the way that one's risk can change as these panels are updated.
Citation for the book:
The $1,000 Genome: The Revolution in DNA Sequencing and the New Era of Personalized Medicine
Kevin Davies (Author)
http://www.amazon.com/The-000-Genome-Revolution-Personalized/dp/1400148502
My tag 1kgenome0mg and search of further personal notes (https://mail.google.com/mail/u/0/#search/1kgenome0mg)
