Doug Robinson (JMP Academic Division, SAS Institute) is giving a presentation of the JMP Genomics software from SAS illustrating data analysis for genetics, expression, and copy number variation studies. Agenda includes: CNV analysis, merging CNV data sets of continuous traits, and QC, analysis, and downstream applications of expression studies.
A tip of the hat to @JVJAI for pointing out this interesting looking paper in AJHG. ROADTRIPS: Case-Control Association Testing with Partially or Completely Unknown Population and Pedigree Structure Timothy Thornton and Mary Sara McPeek Department of Biostatistics, University of Washington. Abstract: Genome-wide association studies are routinely conducted to identify genetic variants that influence complex disorders.
Department of Biostatistics Seminar/Workshop Series: Statistical Methods for DNA Resequencing Analysis in Disease-Gene Studies Wenyi Wang, Ph.D., Faculty Candidate Stanford Genome Technology Center, UC Berkeley Statistics 2:00-3:00pm Monday, February 15, 2010 MRB III Room 1220 Intended Audience: Persons interested in applied statistics, statistical theory, epidemiology, health services research, clinical trials methodology, statistical
Frank Harrell is teaching his 3-session short course on regression modeling strategies using R here at Vanderbilt next month. Frank is a professor and chair of the Vanderbilt Biostatistics Department, and the author of several massively popular R libraries, including Design, rms, and the indispensable Hmisc.
The 2010 Cancer Biostatistics Workshop seminar series begins next Friday with a workshop by Ayumi Shintani on sample size estimation and power analysis. Here's the entire 2010 workshop schedule. Be sure to check out my previous post on software for power calculations in genetic analysis.
Often when presenting statistics from a candidate gene study, or a region of interest from a genome-wide association study, it is useful to see various SNP-wise values in the context of linkage disequilibrium patterns.
R is a great tool with lots of resources for genetics, genome-wide association studies, and many other biological applications. We've covered several places to find help in R in the past, but if you're still apprehensive about diving into R's command-line interface, fear not. The R commander is a graphical user interface (GUI) for R that works under Windows, Linux, and Mac.
At this week's R clinic Frank Harrell will unveil the new rms (Regression Modeling Strategies) package that is a replacement for the R Design package. He will demonstrate the differences with Design, especially related to enhanced graphics for displaying effects in regression models. Frank will also discuss the implementation of quantile regression in rms.
This handy introduction comes from UCLA's Statistical Computing webbook on logistic regression. If you're familiar with linear regression but you've never used logistic regression before, this is a good place to start.
For readers at Vanderbilt: At yesterday's R course I found out that Theresa Scott in the Biostatistics department holds a weekly R clinic and encourages new R users who want to learn more to bring any questions about R, or even your own code and data. The R clinic is held weekly on Thursday from 2:00-3:00 in MCN.