ChIP-Seq Data Analysis Workshop (2-day)
When: Nov. 18th, 2014 - Nov. 19th, 2014 9:30 am - 4:30 pm
To Know
About this Class
Day 1 - AM (9:30-12:30) Introductory Lecture
(Peter FitzGerald, PhD - CCR, NCI)
-
Introduction
- Historical Perspective and Technical Variations
- Experimental methodology
- Comparison to ChIP-Chip
-
Data Analysis
- Experimental Design
- Quality Control
- Peak Calling (Different methodologies)
- Major Sources of Error
- Causes of Fail Experiments
- Validation Methods
-
Sequence Specific Binding
- Identification of Motifs
- Overexpressed sequences
- Pathways
-
Resources
- Public Repositories
- Literature References
- Software listings
Day 1 - PM (1:30-4:30) Introduction to Genomatix
The Genomatix Mining Stations (GMS) and the Genomatix Genome Analyzer (GGA) at the NCI
(Susan Dombrowski, PhD - Genomatix)
- The basics of these tools
- Importing data and mapping of NGS data on the GMS
Day 2 - AM (9:30-12:30) Genomatix Continued
(Susan Dombrowski, PhD - Genomatix)
- Import of data to the GGA
-
Automated, Complete Workflow for ChIP-Seq Analysis
- Peak Finding
- Read and Peak Classification
- Sequence Extraction
- TFBS overrepresenation
- Definition of new TFBS
-
Downstream Application Areas
- Position Correlation with ENCODE ChIP-Seq data
- Annotation of binding regions: target prediction
- Pathway analysis of potential TF targets
(Chongzhi/George Zang, PhD - Dana-Farber Cancer Institute, Harvard School of Public Health)
Cistrome (cistrome.org) is a web-based platform for ChIP-chip and ChIP-seq data analysis and integration. “Cistrome” refers to the in vivo genome-wide location of a transcription factor or a histone modification, which can be characterized using ChIP-chip or ChIP-seq. In this training session, I will introduce the basic functions of Cistrome analysis pipeline and the recently launched Cistrome dataset browser, which has collected over 12,000 public ChIP-seq datasets. Then I will give a practical example to analyze a ChIP-seq dataset using a series of tools on Cistrome. The practice will include:
- ChIP-seq peak calling using MACS
- ChIP-seq integrative analyses
- ChIP-seq and gene expression data integration using BETA
- Investigate public ChIP-seq data using Cistrome Dataset Browser
UCSC Demo lnks