HSLS MolBio Workshops

This is a two-part workshop. Part1, the morning session (10 am - 12 pm) provides a brief introduction to techniques, platforms, and methods used in chromatin profiling experiments, including Transcription Factor / Histone ChIP-Seq and ATAC-Seq. The afternoon session (1 pm - 3 pm) focuses on hands-on data analysis practice using HSLS-licensed CLC Genomics Workbench and TRANSFAC/Match software.

Participants will learn how to

• import NGS reads from an NCBI GEO dataset
• align ChIP-Seq reads to a reference genome
• identify narrow and broad peaks from aligned ChIP-Seq data
• visualize and summarize the output of ChIP-Seq results
• identify enriched sequence motifs present in peak regions and search for the presence of known transcription factor binding motifs using TRANSFAC/Match software 

Target Audience

Experimental biologists seeking to analyze ChIP-Seq data generated through experiments or retrieved from a repository such as GEO. The software covered in the workshop operates through a user-friendly, point-and-click graphical user interface, so neither programming experience nor familiarity with the command line interface is required.

Powerpoints

• ChIP-Seq data analysis with CLC Genomics Workbench
• ChIP-Seq data analysis with PartekFlow

Data Download

• RUNX1_AI.bed (Annotated Peaks filtered by p-value<1E-6): transcription factor (RUNX1) ChIP-seq data downloaded from GEO for software demonstration
• RUNX1_DMSO.bed (Annotated peaks filtered by p-value<1e-6):  control sample for transcription factor (RUNX1) ChIP-seq data downloaded from GEO for software demonstration
• ChIP-Seq (TF/Histone) : NCBI GEO - GSE101789; transcription factor and histone ChIP-seq dataset 
• ATAC-Seq : NCBI GEO - GSE101790; ATAC -seq dataset for software demonstration
• Encode Blacklists (human/mouse); a comprehensive set of regions in the human, and mouse genomes that have anomalous, unstructured, or high signal in next-generation sequencing experiments independent of cell line or experiment. The removal of the ENCODE blacklist is an essential quality measure when analyzing functional genomics data.

Software Registration

• CLC Genomics workbench: to analyze and visualize next-generation sequencing (NGS) data.
• CRC HPC allocation: request for the center for research computing hosted HPC allocation

• PartekFlow: provides software analysis solution for next-generation sequencing data applications.

Videos

• Introduction to ChIP-Seq (StatQuest)
• How to connect with CRC-CLC server
• How to import FASTQ reads into CLCGW software
• How to add metadata to imported reads 

Documentations

• ChIP-Seq data analysis with CLCGW - download ChIP-sequencing tutorial (PDF)
• ATAC-seq data analysis guide (Harvard) 
• ENCODE Data processing pipeline for ChIPSeq 

• ChIP-Seq or ATAC Seq analysis by Partek flow   

• Cistrome db: an integrative platform for transcriptional regulation studies
• Ensembl Reference Seq Download: download organism's reference genome via a browser from this FTP site
• European Nucleotide Archive; provides a comprehensive record of the world’s nucleotide sequencing information
• Gene Regulatory Elements (GeneHancer) - GeneCards: a novel database of human enhancers and their inferred target genes, in the framework of GeneCards.
• Gene Regulatory Elements (GeneHancer) - UCSC Browser: a novel database of human enhancers and their inferred target genes, available via a genome browser.
• Transfac/Match (GeneXplain): a transcription factor database
• Venn Diagram Creator: a web-based tool to draw custom Venn diagrams.

Key References

• Pulikkan JA, Hegde M, Ahmad HM, et al. CBFβ-SMMHC Inhibition Triggers Apoptosis by Disrupting MYC Chromatin Dynamics in Acute Myeloid Leukemia. Cell. 2018;174(1):172-186.e21. doi:10.1016/j.cell.2018.05.048
• Fishilevich S, Nudel R, Rappaport N, et al. GeneHancer: genome-wide integration of enhancers and target genes in GeneCards. Database (Oxford). 2017;2017. doi:10.1093/database/bax028
• Amemiya HM, Kundaje A, Boyle AP. The ENCODE blacklist: identification of problematic regions of the genome. Sci Rep. 2019;9(1):9354. doi:10.1038/s41598-019-45839-z 

Attribution

Please include the following statement in the acknowledgments section for all publications, posters, and presentations: 

[Software name] licensed through the Molecular Biology Information Service of the Health Sciences Library System, University of Pittsburgh (RRID:SCR_011975) was used for data analysis.

If you used the Pitt-CRC server for CLC Genomics Workbench, then please also include the following text in the acknowledgments section for all publications, posters, and presentations: 

This research was supported in part by the University of Pittsburgh Center for Research Computing through the resources provided.

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