ChIP- and DNase-seq data analysis workshop - Training
|Date:||17.09.2014 10:00 - 20.09.2014 17:00|
Several trainers as indicated in the program.
The workshop is kindly sponsored by the EU FP7 AllBio project, which aims to bring biologists and bioinformaticians together for the effective exploitation of high-throughput data. AllBio provides 15 travel bursaries of 500 euros for early stage researchers (PhD students or researchers with less than 8 years of experience after obtaining PhD).
10:00-17:00 Hands-on module 1: "ChIP-seq data analysis with R/Bioconductor"
This practical tutorial covers peak calling, annotation, motif discovery and differential binding analysis of ChIP-seq data. The analysis tools used in the exercises include several R/Bioconductor packages such as chipseq, Biostrings, BSgenome, DESeq and Diffbind, so participants need to have experience in R programming.
Borbala Mifsudi (UCL, UK)
Filipe Tavares-Cadete (Instituto de Biologia Experimental Tecnológica, Portugal)
10:00-17:00 Hands-on module 2: "ChIP- and DNase-seq data analysis with Chipster"
This practical tutorial covers quality control, alignment, peak calling, annotation, motif discovery and genome browser visualization. The free, user-friendly Chipster software is used in the exercises, so no previous knowledge of Unix or R is required, and the tutorial is thus suitable for everybody.
Eija Korpelainen (CSC): ChIP- and DNase-seq data analysis with Chipster: slides, exercises
Hashem Koohy (Babraham Institute, UK): Peak calling with MACS and F-seq
- 10:00-10:05 Eija Korpelainen (CSC): Welcome
- 10:05-10:50 Borbala Gerle (UCL, UK): ChIP-seq data and analysis
- 10:50-11:20 Teemu Daniel Laajala (University of Turku, Finland): Comparison of peak callers for ChIP-seq data
- 11:20-12:00 Jan Grau (Martin Luther University Halle-Wittenberg, Germany): Discriminative de novo motif discovery from high-throughput data
- 12:00-13:00 Lunch
- 13:00-13:40 Endre Barta (University of Debrecen, Hungary): Transcription factor binding site and regulatory SNP meta-analysis based on ChIP-seq data
- 13:40-14:20 Hashem Koohy (Babraham Institute, UK): Comparison of peak callers used for DNase-seq data
- 14:20-15:00 Jason Piper (University of Warwick, UK): Identification of digital genomic footprints from DNase-seq data
This tutorial demonstrates how NGS analysis tools can be run using tens or hundreds of computing cores at CSC. In addition to the cluster environment, also the cloud environment Pouta and the FGI grid are discussed. Basic knowledge of Unix is recommended for this session. This session is relevant for participants who have access to CSC's computing environment.
Material: slides, exercises
Trainer: Kimmo Mattila (CSC)
This practical tutorial covers alignment, peak calling, annotation and motif discovery of ChIP-seq data. The analysis tools used in the exercises include several command line tools such as BWA, MACS, MEME and Homer, so participants need to be familiar with Unix.
Material: slides, exercises
Endre Barta (University of Debrecen, Hungary)
Gergely Nagy (University of Debrecen, Hungary)
14:00-17:00 Hands-on module 5: "DNase-seq data analysis using command line tools and introduction to pyDNase"
This practical tutorial covers peak calling with MACS and F-seq and detection of DNase-seq footprints. It also introduces pyDNase, a Python package for analysing DNase-seq data. Participants need to be familiar with Unix. For those that would like to do more bespoke analyses using the pyDNase library, Python experience is required.
Material for peak calling
Material for footprinting
Jason Piper (University of Warwick, UK)
Hashem Koohy (Babraham Institute, UK)