Upcoming Classes & Workshops
2012
Advanced R / Bioconductor Workshop on High-Throughput Genetic Analysis
February 27-28, 2012
Fred Hutchinson Cancer Research Center - Seattle, WA
BIO 503 - Programming & Stat Modeling (January 2012)
Harvard School of Public Health, Winter 2012
Dr. A. Culhane
1.250 Credit hours
2011
More courses
Classes and Teaching Archive
2011
July 2011 - Statistical Analysis of Genomics Data at CSHL
Lecture and tutorial on Reproducible Research and Sweave and GeneSet analysis
June 2011 - Reproducible Research and Sweave
Half day course introducing Sweave
May 2011 - Introduction to R and Bioconductor
1.5 day introductory course to R and Bioconductor
Jan 2011 - BIO 503 - Programming & Stat Modeling
Harvard School of Public Health, Winter 2011
Seminars. Five 3-hour sessions during WinterSession
This course is an introduction to R, a powerful and flexible statistical language and environment that also provides more flexible graphics capabilities than other popular statistical packages. The course will introduce students to the basics of using R for statistical programming, computation, graphics, and modeling.
2010
Feb 2010- Bio506 Introduction to Computational Biology
I gave a lecture on GeneSet Analysis and GeneSigDB as part of this course.
Jan 2010- Bio503- Introduction to Programming and Statistical Modeling in R
Harvard School of Public Health, Winter 2010
Dr. A. Culhane and Dr. S. Bentink
1.25 credits
Seminars. Five 3-hour sessions during WinterSession
This course is an introduction to R, a powerful and flexible statistical language and environment that also provides more flexible graphics capabilities than other popular statistical packages. The course will introduce students to the basics of using R for statistical programming, computation, graphics, and modeling.
2008
Bio503 Introduction to Programming and Statistical Modeling in R
Harvard School of Public Health, Winter 2008
Dr. A. Culhane
1.25 credits
Seminars. Five 3-hour sessions during WinterSession
This course is an introduction to R, a powerful and flexible statistical language and environment that also provides more flexible graphics capabilities than other popular statistical packages. The course will introduce students to the basics of using R for statistical programming, computation, graphics, and modeling.
