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Math 283  —  Fall 2018
Statistical Methods in Bioinformatics
Calendar

Updated 10/17/18


Note: This calendar is approximate and is subject to revision.
Chapter numbers are for the class textbook by Ewens & Grant.
Slides are posted in advance for most lectures, but are subject to revision.

Discussion Sessions with T.A. Bokan Bao (dates TBA)
Week 2 Friday October 12, 2-3:30 p.m. in AP&M 6402
  • Tutorial on Matlab and R. Worksheets: Matlab, R
Week 5 or 6 Location and date TBA
  • Midterm review
Week 7 or 8 Location and date TBA
Week 10 or 11 Location and date TBA
  • Final exam review
Lectures: Week 1
Mon. Oct. 1 Website, syllabus, and background survey
 
Review of discrete random variables (slides 1-25): [slides revised]
  • Probability density functions (Sec. 1.2)
  • Joint pdf (2.1, 2.2, 2.5)
  • Conditional pdf (2.6)
  • Combinations and permutations
  • Mass spec
  • Binomial (1.3.2) and multinomial (2.4.2) distributions
Wed. Oct. 3
  • continued (slides 27-45)
  • Expected values (1.4) and Variance (1.5)
  • Geometric distribution (1.3.5) and Negative Binomial Distribution (1.3.6)
Week 2
Mon. Oct. 8
  • continued (rest of slides)

Mendel's Laws and Gene mapping:
  • Note that we are finishing last week's slides, and then two additional sets of slides are posted for today's lecture.
  • Mendel's Laws, crossovers and recombination rates, Haldane's Mapping Function (slides)
  • Poisson distribution and crossovers (Ewens & Grant 1.3.7, 4.1-4.2) (slides 1-17)
Wed. Oct. 10
  • Poisson distribution, continued (slides 18-22)
    For now, skip slides 23-31 on the Exponential and Gamma Distributions; we will cover these topics later.

Lander-Waterman shotgun sequencing statistics (5.1) (slides)
Week 3
Mon. Oct. 15 Maximum Likelihood Estimates (8.1-8.3) (slides)

Continuous distributions (slides 1-14)
  • Continuous distributions (1.8-1.10, 4.3)
  • Uniform distribution
  • Cumulative distribution function
Wed. Oct. 17
  • Exponential and gamma distributions (1.10, 4.3) (slides 14-end)

Normal distribution and Central Limit Theorem (1.10, 2.10) (slides 1-23)
  • Normal distribution
  • Approximating binomial distribution by normal distribution
Week 4
Mon. Oct. 22
  • continued (rest of slides)
  • Central Limit Theorem

Hypothesis testing, intro: (slides)
  • Distribution of the maximum of n random variables (2.11)
  • Long repeats (5.4) and hypothesis tests (3.4)
Wed. Oct. 24
  • continued (rest of slides)

Hypothesis tests for the normal distribution: (slides)
  • z and t-tests for the mean of a normal distribution (3.5.1-3.5.2)
Week 5
Mon. Oct. 29
  • continued (rest of slides)
  • Confidence intervals (3.3.2)
  • Binomial tests for p
  • Choosing n to control Type I and Type II errors

Non-parametric hypothesis tests: (slides)
  • Probability generating functions intro (1.7, 1.11, 2.3)
  • Wilcoxon signed rank test (3.8.3)
  • Mann-Whitney test (3.8.2)
Wed. Oct. 31
  • Non-parametric hypothesis tests, continued (slides)
Week 6
Mon. Nov. 5
  • Non-parametric hypothesis tests, continued (rest of slides)

Microarrays: (slides)
Wed. Nov. 7 Midterm
Week 7
Mon. Nov. 12 Microarrays, continued (rest of slides)

Chi-squared hypothesis tests: (slides)
  • Chi-squared (1.10.5) and F-tests (9.5.2) for variance.
Wed. Nov. 14
  • Chi-squared tests for goodness-of-fit (3.5.4) and association (3.5.5) (rest of slides)

Frequencies of words:
  • Number of occurrences of a word (5.7) and a motif (5.9) allowing overlaps (slides)
Week 8
Mon. Nov. 19
  • continued (rest of slides)

Markov chains (4.5-4.9, 11.{1,2,4,6}):
Wed. Nov. 21
Week 9
Mon. Nov. 26
  • Markov chains, continued (rest of slides)

Wed. Nov. 28 Principal Components Analysis (slides)
Week 10
Mon. Dec. 3
  • PCA, continued (rest of slides)

Linear Regression (8.4.3) (slides)
Wed. Dec. 5
  • Demo 1 and rest of slides

Analysis of Variance (9.5-9.7, 13.3.7) (slides)
Week 11
Wed. Dec. 12 Final exam, 3-6 p.m.