1. STAT115 STAT225 BIST512 BIO298 - Intro to Computational Biology

2. March 28, 2012 Daniel Fernandez Alejandro Quiroz

3. STAT115 STAT225 BIST512 BIO298 - Intro to Computational Biology 1 st ACT Review of the paper Cistrome Homework Help Q2 INTERLUDE Electronic music with DJ CR (10 min) 2 nd ACT Peak Callers Homework help Q1

4. STAT115 STAT225 BIST512 BIO298 - Intro to Computational Biology

5. Layers of chromatin organization in mammalian cells 5Zhou et al, 2011

6. STAT115 STAT225 BIST512 BIO298 - Intro to Computational Biology Existing technologies for genomewide mapping of chromatin organization 6Zhou et al, 2011 Sequencing BS-seq MeDIP-seq MNase-seq CATCH-IT ChIP-seq 3C, Hi-C

7. STAT115 STAT225 BIST512 BIO298 - Intro to Computational Biology ChIP-seq maps of histone modifications reveal functional elements 7Zhou et al, 2011

8. STAT115 STAT225 BIST512 BIO298 - Intro to Computational Biology ChIP-seq maps chromatin features using crosslinking and antibodies 8

9. STAT115 STAT225 BIST512 BIO298 - Intro to Computational Biology Histone modification patterns characterize promoter classes 9Zhou et al, 2011

10. STAT115 STAT225 BIST512 BIO298 - Intro to Computational Biology Histone modification patterns characterize “states” for genomic elements 10Zhou et al, 2011

11. STAT115 STAT225 BIST512 BIO298 - Intro to Computational Biology Histone modifications defines “states” 11Ernst et al, 2011

12. STAT115 STAT225 BIST512 BIO298 - Intro to Computational Biology Do histone modification signatures associate with chromatin proteins and nuclear features? 12Zhou et al, 2011

13. STAT115 STAT225 BIST512 BIO298 - Intro to Computational Biology

17. The Cistrome Understanding Genetic Regulation CisTrOme, stands for Cis-acting regulatory elements searched across, Trans, the whole genOme. –Visit and register at http://cistrome.org/http://cistrome.org/ The objective is to map/identify the binding regions of a transcription factor across (trans) the genome in order to understand the regulatory mechanisms of gene expression in the chromosome where the gene is located (cis).

18. STAT115 STAT225 BIST512 BIO298 - Intro to Computational Biology Types of Data and Peak – Calling Methods Chip-Chip data (Chip on Chip) –Affymetrix one color arrays –Nimble two color arrays Chip-Seq data (Chip and NGS) –Sequencing data (Illumina, Roche, 454) MACS Model based Analysis for Chip-Seq MA2C Model based Analysis for 2-Color arrays MAT Model based Analysis for Tiling arrays

19. STAT115 STAT225 BIST512 BIO298 - Intro to Computational Biology Typical Chip-Seq Pipeline

20. STAT115 STAT225 BIST512 BIO298 - Intro to Computational Biology Typical Chip-Seq Pipeline

21. STAT115 STAT225 BIST512 BIO298 - Intro to Computational Biology Typical Chip-Seq Pipeline

22. STAT115 STAT225 BIST512 BIO298 - Intro to Computational Biology Chip-Seq Analysis tools

23. STAT115 STAT225 BIST512 BIO298 - Intro to Computational Biology Typical Chip-Seq Pipeline

24. STAT115 STAT225 BIST512 BIO298 - Intro to Computational Biology Chip-Seq Peak Caller - MACS

25. STAT115 STAT225 BIST512 BIO298 - Intro to Computational Biology Pipeline for MACS

26. STAT115 STAT225 BIST512 BIO298 - Intro to Computational Biology Chip-Seq Analysis tools