Introduction to Data Analysis in Natural Resources (NR-554): Using SAS to examine, summarize and analyze research data. The course is offered in Spring semester.

Quantitative Forest Genetics Methods (FOR-728): With Gary Hodge. Applications of quantitative genetic methods in forest tree breeding, marker aided selection and genetic research.

GN 703 Population and Quantitative Genetics guest lecture notes - Response to short-term selection

College teachers

Click picture to see which type of college professor is your favorite (By Matt Groening)

Some notes on SNP markers data analysis and genome-wide selection methods in tree breeding (PDF).

Course notes for analysis of binary and count data. Solved examples for forest tree diseases.

Some Course notes and SAS examples for progeny test data analysis in tree breeding:

You need to have at least medium level SAS programming experience to run most codes.

* SAS tips for data manipulation

* Data examination using SAS (PDF).

* Half-sib progeny data analysis using SAS (PDF).

* Genetic Correlations and Correlated Response (PDF)

* Analysis of Diallels using SAS (PDF).
If you really need to analyze Diallel Mating Designs routinely, think about ASReml. It is much easier.


Hike in Goreme
With a group of students from the College of Natural Resources, we had Study Abroad Program in Turkey In June 2007. Hiking in Pigeon Valley (Goreme, Turkey).

We had a another trip in June-July 2009 to Turkey. Here is a picture from Black Sea Mountains. Click here to see more pictures


Department of Forestry & Environmental Resouces

NC State University Libraries






Fikret Isik

Drawing by Deniz Cigdem Ceylan (6 years old at the time. June 2007).

  Fikret T. Isik
Research Associate Professor of Quantitative Forest Genetics

1019 Biltmore Hall
North Carolina State University,
Department of Forestry and Environmental Resources

E-Mail: fisik@ncsu.edu
Tel: 919-410-6072

Fax: 919-515-3169,


Statistical consultant of College of Natural Resoures.
Click here to see some examples of data analysis reports.


Current Research Projects

Marker Aided Selection in Trees (2007-2011, USDA): Discovery and genotyping of single-nucleotide polymorphisms have become affordable in recent years, but methods for applying these technologies to tree improvement programs are still lacking. As part of the Conifer Translational Genomics Network (lead by David Neal), my current research focuses on using markers in tree breeding, specifically in prediction of breeding values (using the mixed model theory and BLUP) in Pinus taeda breeding populations (with Ross Whettena and Steve McKeand).

Genetic Improvement of Pine for Fusiform Rust Disease Resistance (Forest Industry): A major threat to pine plantations in the southern USA. Research on fusiform rust disease includes new disease resistant gene discovery in elite pine clones, utilization of resistance genes in pine breeding programs (gene stacking, genotyping and association with disease occurance) and study of host pine genotypes by pathogen interactions (with Ross Whetten, Steve McKeand, Saul Garcia).

Regulation and Modeling of Lignin Biosynthesis (2009-2012, NSF): The mechanisms of regulation of lignin biosynthesis are largely unknown. The project seeks to build models to describe how the pathway is regulated and to reveal new control mechanisms, leading to lignin polymers. The project will use the model woody plant, Populus trichocarpa (black cottonwood) and a systems approach including advanced quantitative methods of genomics, proteomics, biochemistry and structural chemistry, to provide a comprehensive analysis of the regulation of lignin biosynthesis (with Vincent Chiang, Ron Sederoff, Joel Ducoste and John Ralph).


Some recent publications:

Isik F., H. V. Amerson, R. W. Whetten, S. A. Garcia, B. Li, and S. E. McKeand. 2008. Resistance Assessments of Elite Loblolly Pine Families to Fusiform Rust Inocula in Greenhouse Testing. Canadian J. Forest Research 38:2687-2696.

Isik, F., M. Gumpertz, B. Li, B. Goldfarb, and X. Sun. 2008. Analysis of cellulose microfibril angle using a linear mixed model in Pinus taeda clones. Canadian J. Forest Research 38:1676-1689.

Isik, F., B. Li, B. Goldfarb, S.E. McKeand. 2008. Prediction of wood density breeding values of Pinus taeda elite parents from unbalanced data: A method for adjustment of site and age effects using common checklots. Annals of Forest Science 65: 406-413.

Isik, F., D.D. Boos, B. Li. 2005. The distribution of genetic parameter estimates and confidence intervals from small disconnected diallels. Theoretical and Applied Genetics 110:1436-2243


An interview (inTurkish) with journal ORMAN VE AV (April 2011).

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Last modified on: September 14, 2012