Page Title

140.668 Special Topics in Genetics and Genomics (2008)

Instructor

Hongkai Ji

Contact

Office: 615 N. Wolfe St., Rm. E3638

Office hours: Thursday 3:00-4:00pm

Office Phone: 410-955-3517

Email: hji@jhsph.edu

Class times

Monday 10:30 - 11:50am

Wednesday 10:30 - 11:50am

Location

Wolfe W4013

Syllabus

[PDF]

Final Project

Due date: Dec 22, 5pm.

Page limit: <= 6 pages; <=3000 words, <= 5 display items (including figures and tables).

Lecture Slides & Readings

Oct 27 (Mon): Course overview, molecular biology, bioinformatics, roles of statistics (Ji)

Slides: Introduction

Readings:

1. Ji H and Wong WH (2006) Computational biology: towards deciphering gene regulatory information in mammalian genomes. Biometrics, 62: 645-663.

Oct 29 (Wed): Microarray analysis, normalization, preprocessing, probe effect, background correction (Irizarry)

Lecture Slides: Probe level data, Normalization

R code: 1, 2

Readings: NA

Nov 3 (Mon): Differential gene expression, gene set analysis, gene ontology (Irizarry)

Slides: Differential expression

Readings:

Nov 5 (Wed): Multiple testing, false discovery rate, pooling information (Ji)

Slides: (See Nov 3 Slides)

Readings:

1. Benjamini, Y. and Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of Royal Statistical Society, Series B 57, 289-300.

2. Smyth, G. K. (2004). Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. Statistical Applications in Genetics and Molecular Biology 3(1), Article 3.

Nov 10 (Mon): Motif discovery, Gibbs motif sampler (Ji)

Slides: Motif analysis

Readings:

1. Lawrence, C. E., Altschul, S. F., Boguski, M. S., Liu, J. S., Neuwald, A. F., and Wootton, J. C. (1993). Detecting subtle sequence signals: a Gibbs sampling strategy for multiple alignment. Science 262, 208-214.

2. Jensen, S. T., Liu, X. S., Zhou, Q., and Liu, J. S. (2004). Computational discovery of gene regulatory binding motifs: a Bayesian perspective. Statistical Science 19, 188-204.

3. Bailey, T. L. and Elkan, C. (1994). Fitting a mixture model by expectation maximization to discover motifs in biopolymers. In Proceedings of the Second International Conference on Intelligent Systems for Molecular Biology, 28-36. AAAI Press, Menlo Park, California

Nov 12 (Wed): Motif discovery, cont. (Ji)

Slides: same as before

Nov 17 (Mon): Cis-regulatory modules, module sampler, phylogenetic footprinting (Ji)

Slides: Module discovery

Readings:

1. Zhou, Q. and Wong, W.H. (2004). CisModule: De novo discovery of cis-regulatory modules by hierarchical mixture modeling. Proc. Natl. Acad. Sci. USA, 101: 12114-12119.

Nov 19 (Wed): Tiling array, background correction, peak detection, HMM (Ji)

Slides: Tiling array and ChIP-chip

Readings:

1. Ji, H. and Wong, W.H. (2005) TileMap: create chromosomal map of tiling array hybridizations. Bioinformatics, 21:3629-3636

2. Johnson WE, Li W, Meyer CA*, Gottardo R, Carroll JS, Brown M and Liu XS (2006) Model-based analysis of tiling-arrays for ChIP-chip. Proc. Natl. Acad. Sci. USA 103 12457-12462.

Nov 26 (Wed): SNP arrays, genotyping, copy number variations (Scharpf)

Slides: SNP array and copy number variations

Nov 24 (Mon): Exon arrays, probe selection, gene-level expression, alternative splicing (Ji)

Slides: Exon array

Readings:

1.Xing, Y., Kapur, K., Wong, WH. (2006) Probe selection and expression index computation of Affymetrix Exon Arrays. PLoS ONE. 1(1):e88

2. Kapur, K., Xing, Y., Ouyang, Z., Wong, WH. (2007) Exon arrays provide accurate assessments of gene expression. Genome Biology. 8:R82

3. Xing, Y., Stoilov, P., Kapur, K., Han, A., Jiang, H., Shen, S., Black, DL., Wong, WH. (2008) MADS: a New and Improved Method for Analysis of Differential Alternative Splicing by Exon-tiling Microarrays. RNA.14(8):1470-1479 .

Dec 1 (Mon): Association studies (Ruczinski)

Resources for GWAS: Link

Dec 3 (Wed): Next-generation sequencing, data and models (Ji)

Slides: Sequencing

Readings:

1. Jay Shendure and Hanlee Ji (2008) Next-generation DNA sequencing. Nature Biotechnology 26, 1135-1145.

2. Ji H, Jiang H, Ma W, Johnson DS, Myers RM and Wong WH (2008) An integrated software system for analyzing ChIP-chip and ChIP-seq data. Nature Biotechnology. 26: 1293-1300.