This weekend features one of my all-time favorite sporting events: the golf US Open (plus Father’s Day on Sunday provides a convenient guilt-free excuse to actually watch it). This year, the tournament is held at the Bethpage Black course just outside of New York City. It has a classic sign:
For about a year now, I’ve been having trouble with my faithful Craftsman Eager-1 push mower, which I bought at Sears about 15 years ago. The daggum thing starts up fine but then cuts off after about 2 seconds. This has led me to adopt the following algorithm: 1. Press
Sometimes, I’m totally astounded at how much our science has advanced since my days as a graduate student. Back then, the closest anyone got to “genomic” studies of eukaryotic organisms involved “melting” DNA and watching it come back together using CoT curves. Cloning and sequencing a single cDNA could get
Thanks for the enlightening comments to my blog post "I Like 3-D Pie Charts" and for the new graphs. While the bar charts from Joe and John are very nice, I prefer vertical bars because of their connection with the gravity orientation of trees, mountains, buildings and of course cell-phone
So you know I’m a faithful left-brained statistician who makes every attempt to adhere to the highest professional standards of data visualization and analysis. Graphics luminaries like Edward Tufte and Stephen Few have made very valuable contributions to the field, and I bow to their wisdom. But I have a
My youngest daughter was recently watching a rerun of Home Improvement featuring Tim “The Tool Man” Taylor and his mock TV show Tool Time. She said “Dad, you and Tim both seem to get into a lot of trouble when playing with power tools.” My wife added that throwing a
When asked if I miss being the lead developer of mixed model software at SAS, I usually reply “yes and no.” The “yes” comes from feeling very fortunate to have been involved with this powerful methodology throughout my nearly 20 years at SAS and a part of the strong legacy
Our goal at JMP Genomics has always been to make it easier for you, the genomics scientist, to analyze and interpret your data. The JMP Genomics User Guide has been there to help you choose which analytical process(es) best meet your needs by showing you what you need to run
Scientific Computing has published a review of JMP Genomics 3.2 by statistician John Wass titled "The Magic of Genomics." Wass also evaluated an early version of JMP Genomics in 2006. JMP Genomics has evolved fast and come a long way since those early days, and Wass’ review recognizes that –
The rapid growth of SNP data sets due to the introduction of 1 million SNP chips from Affy and Illumina and NextGen sequencing has led to larger and larger data sets. While JMP Genomics 3.1 supported analysis of SNP data sets as large as 1 million SNPs x 4,000 individuals,