Course Director: Aik Choon Tan, Ph.D.

Course Instructors/Tutors:
Jihye Kim, Ph.D.
Hyunmin Kim, Ph.D.

Class: Tuesday 1pm - 5pm
Venue: RC1N 1309 (P18 CTL-1309)

Course Syllabus

1. INTRODUCTION - 9/4/18

   • [SLIDES]

   • [WORKSHOP SLIDES]

   • Related Perl Scripts and Data [Link]

   • Unix commands (cheat sheet) [Download]

   • For MAC user, Text Wrangler is a good text editor [Download]
   
   
2. DATA MINING CONCEPTS - 9/11/18

   • [SLIDES]

   • [WORKSHOP SLIDES]

   • Download CLUSTER 3.0 from (http://bonsai.hgc.jp/~mdehoon/software/cluster/software.htm).
   • Link to CLUSTER 3.0 Manual [Manual]

   • Download CDT HERE

   • Download GTR HERE

   • Download ATR HERE

   • Download Java TreeView from (http://jtreeview.sourceforge.net/).

   • Java for OS X2015-001 (Legacy Java 6 runtime) [Download]

   • Link to CLASS02 Workshop materials and Assignment 2 [LINK]
   
   
3. GENE EXPRESSION ANALYSIS I - CANDIDATE GENE APPROACH - 9/18/18

   • [SLIDES]

   • Link to CLASS03 Workshop materials and Assignment 3 [LINK]

     Reading materials:

   • SAM paper: Tusher, Tibshirani, Chu. (2001). Significance analysis of microarrays applied to the ionizing radiation response. PNAS 98(9):5116-5121. [PDF]
   • FDR calculation in high-throughput genomics data: Xie, Whitehurst, White (2007). A practical efficient approach in high throughput screening: using FDR and fold change. Nature Protocol Exchange. [Link]
   • Comparisons of various methods: Jeanmougin, de Reynies, Marisa, Paccard, Nuel, Guedj. (2010). Should we abandon the t-test in the analysis of gene expression microarray data: a comparison of variance modeling strategies. PLoS ONE. 5(9): e12336. [PDF]

4. GENE EXPRESSION ANALYSIS II - GENE SET ANALYSIS - 9/25/18

   • [SLIDES]

   • [WORKSHOP SLIDES]

   • Link to CLASS04 Workshop materials and Assignment 4 [LINK]

     Reading materials:

   • Mootha et al. (2003). PGC-1-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat. Genetics. [PDF]
   • GSEA Paper: Subramanian et al. (2005). Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. PNAS. [PDF].
   • GSEA User Guide [Link]
   • Emmert-Streib, Glazko (2011). Pathway Analysis of Expression Data: Deciphering Functional Building Blocks of Complex Diseases. PLoS Comp. Biol.[PDF]
   • Khatri, Sirota, Butte (2012). Ten Years of Pathway Analysis: Current Approaches and Outstanding Challenges. PLoS Comp. Biol. [PDF]

5. GENE LIST ENRICHMENT ANALYSIS III - TOOLS, DATA INTEGRATION AND VISUALIZATION - 10/9/18

   • [SLIDES]

   • [WORKSHOP SLIDES]

   • Link to CLASS05 Workshop materials and Assignment 5 [LINK]

     CLICK

6. GENE EXPRESSION ANALYSIS IV - PROCESSING, QUERYING AND VISUALIZING GENE EXPRESSION DATA - 10/16/18

   • [SLIDES]

   • [WORKSHOP SLIDES]

   • Link to CLASS06 Workshop materials and Assignment 6 [LINK]

     Reading materials:

   • Irizarry et al. (2003). Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostat. [PDF]
   • Rung & Brazma. (2013). Reuse of public genome-wide gene expression data. Nat. Rev. Genetics. [PDF]
   • Brazma et al. (2001). Minimum information about a microarray experiment (MIAME) - toward standards for microarray data. Nat. Biotech. [PDF]
   • Pavlidis & Noble. (2003). Matrix2png: a utility for visualizing matrix data. Bioinformatics. [PDF]

7. NEXT GENERATION SEQUENCING - INTRODUCTION, ALGORITHMS AND TOOLS - 10/23/18
   • [SLIDES]

   • IGV

   • [WORKSHOP SLIDES]

   • sample1.bam

   • sample5.bam

   • gene_exp.diff

   • BioJupies

   • No Assignment 7.

8. MINING CANCER CELL LINES DATABASES - 10/30/18

   • [SLIDES]

   • [WORKSHOP SLIDES]

   • Link to NCI DTP (NCI-60)

   • Link to COSMIC

   • Link to GDSC

   • Link to CCLE

   • Link to Assignment 8 [LINK]

9. MINING CANCER GENOMICS DATA - 11/6/18

   • [SLIDES]

   • cBioPortal Web Page

10. CONNECTIVITY MAP - 11/13/18

    • [SLIDES]

    • [WORKSHOP]

      Reading materials:

    • Lamb et al (2006). The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease. Science. 313(5795): 1929-1935. [PDF]

    • Subramanian A et al (2017). A next generation connectivity map: L1000 Platform and the first 1,000,000 profiles. bioRxiv. [PDF]

    • Connectivity Map website [LINK]

11. FINAL PROJECT AND PRESENTATION - 11/27/18

    Format: 10 mins presentation.

    • Introduction (motivation, what is the question? what are you trying to solve/find from the data?)
    • Features of your Data sets (either in house and/or public data sets, what kind of data? how do you process the data?)
    • Analysis Plan (what is your plan to tackle the problem bioinformatically? workflow?)
    • Tools that you used in the analysis/mining of your data (list out the tools, some background about the tools etc).
    • Results & Interpretation (what are the results? how do you present your results? how do you interpret the data?)
    • Future Plan & Discussions (what is next? validation in the lab?)
    • Conclusions