Background courses

Following is a list of background courses required for graduate study in statistical genetics. These courses can be waived if a student has completed any equivalent course at UW or elsewhere. Several of the classes are typically offered in the summer quarter.

A student should have completed the following courses:

• CSE 142 Computer Programming for Engineers and Scientists I (4) NW/QSR
  Basic programming-in-the-small abilities and concepts. Highlights include procedural and functional abstraction with simple built-in data type manipulation. Basic abilities of writing, executing, and debugging programs. Not available for credit to students who have completed CSE 210 or ENGR 141. Offered: AWSpS.
• GENOME 371 Introductory Genetics (5) NW
  Explores gene transmission, chromosome mapping, quantitative traits, population genetics, genetic analysis of biological processes. Emphasizes formal genetic mechanisms but includes some molecular techniques, such as restriction mapping, cloning, RFLP analysis. For biological sciences majors. Prerequisite: either CHEM 150, CHEM 152, CHEM 155, or CHEM 221 recommended: BIOL 201. Offered: AWSpS.

and one course from the following:

• GENOME 372 Gene Structure and Function (5) NW
  Explores the structure of genes and chromosomes, the mechanisms and control of transcription and translation, and the molecular mechanisms of mutation, recombination, transposition, and development. Intended for majors in biological sciences. Prerequisite: either BIOL 201 or GENOME 371. Offered: WSp.
• GENOME 453 Genetics of the Evolutionary Process (3) NW: Felsenstein, Kuhner
  Contributions of genetics to the understanding of evolution. Processes of mutation, selection, and random genetic events as they affect the genetic architecture of natural populations and the process of speciation. Emphasis on experimental data and observation, rather than mathematical theory. Prerequisite: either GENOME 371 or GENOME 372.
• GENOME 465 Advanced Human Genetics (4) NW: King, Olson
  Explores genetic analysis of naturally occurring variation in humans; origins and consequences of mutation, as mediated by selection, migration, population structure and drift; approaches to finding human disease genes and characterizing them at the molecular level; relevance of other species to analysis of human genes. Offered: W.

In addition, a student should have completed both a course in probability and a course in statistics which includes both probability models and regression. For example

• STAT 394 Probability I (3) NW
  Sample spaces; basic axioms of probability; combinatorial probability; conditional probability and independence; binomial, Poisson and normal distributions. Prerequisite: either 2.0 in MATH 126 or 2.0 in MATH 136; recommended: MATH 324 or MATH 327. Offered: jointly with MATH 394; AWS.

and

• STAT 390 Probability and Statistics in Engineering and Science (4) NW
  Concepts of probability and statistics. Conditional probability, independence, random variables, distribution functions. Descriptive statistics, transformations, sampling errors, confidence intervals, least squares and maximum likelihood. Exploratory data analysis and interactive computing. Students may receive credit for only one of 390, STAT/ECON 481, and ECON 580. Prerequisite: either MATH 136, MATH 307, or MATH 327; either MATH 205 or MATH 308.. Offered: jointly with MATH 390; AWSpS.