Monday - Classes from 2 to 8 pm Berlin time. Introduction to
epigenomics, and 3D organisation of genomes
Lecture 1
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General processing of Hi-C data
Lab 1
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Step-by-step processing of Hi-C data and integration with
snakemake.
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Use of existing Hi-C processing pipelines and common formats.
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Manipulation and visualisation of sparse matrices using the cooler
package
Tuesday: Application and analysis of Hi-C data
Lecture 2
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Applications of Hi-C data (Scaffolding, 3D QTL, regulatory
genomics)
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Common analysis on Hi-C contact maps and their biological
interpretation
Lab2
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Compute interpretable metrics on the Hi-C contact maps from previous
lesson
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Use existing methods for signal detection in Hi-C data.
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Compare the signals across samplesVisualization techniques for Hi-C derived signals in jupyter notebook
Wednesday: 2-8 pm Berlin time. ChIP-seq analysis
Lecture 3
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Introduction to ChIP-SeqMain uses of ChIP-Seq
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General processing of ChIP-seq data
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Introduction to Bioconductor
Lab 3
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Step-by-step processing of ChIP-Seq data
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Identification of TF-binding site or epigenomic histone modification using
ChIP-seq peak calling
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Identification of motifs and motif enrichment analysis
Thursday: 2-8 pm Berlin time. ATAC-seq
Lecture 4
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Notion of local chromatin accessibility
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Assays to measure chromatin accessibility: a long story of
nucleases
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Why peak callers should be carefully chosen
Lab 4
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Identification of ATAC-seq peaks on multiple samples using
YAPC
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Differential binding analysis and clustering of ATAC-seq
peaks
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Study of chromatin accessibility at promoters with
V-plots
Friday: 2-8 pm Berlin time. Integration and visualization of different
genomics data
Lecture 5
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Types of questions: Classification, description, differential
analysis
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Regulatory states from histone marks
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Identification of transcription factor target genes using RNA-seq and
ChIP-seq
Lab 5
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Crossing results from ATAC-seq with chromHMM
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Integration of ChIP-seq data and RNA-seq data
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Analysis with external databases: GO analysis, protein functional
interactions, ...