ChIP-Seq Peak Callers
2 minute read
ChIP-Seq Workflow
- Read quality assessment, filtering and trimming
- Align reads to reference genome
- Compute read coverage across genome
- Peak calling with different methods and consensus peak identification
- Annotate peaks
- Differential binding analysis
- Gene set enrichment analysis
- Motif prediction to identify putative TF binding sites
Challenge Projects
1. Comparison of peak calling methods
- Run workflow from start to finish (steps 1-8) on ChIP-Seq data set from Kaufman et al. (2010)
- Challenge project tasks
- Call peaks with at least 2-3 software tools, such as MACS2,
slice
coverage calling (Bioc), PeakSeq, F-Seq, Homer, ChIPseqR, or CSAR. - Compare the results with peaks identified by Kaufmann et al (2010)
- Report unique and common peaks among three methods and plot the results as venn diagrams
- Plot the performance of the peak callers in form of ROC plots. As true result set one can use the intersect of the peaks identified by all methods.
- Call peaks with at least 2-3 software tools, such as MACS2,
2. Comparison of peak calling methods
- Similar as above but with different combination of peak calling methods and/or performance testing approach.
References
- Feng J, Liu T, Qin B, Zhang Y, Liu XS (2012) Identifying ChIP-seq enrichment using MACS. Nat Protoc 7: 1728–1740. PubMed
- Kaufmann, K, F Wellmer, J M Muiño, T Ferrier, S E Wuest, V Kumar, A Serrano-Mislata, et al. 2010. “Orchestration of Floral Initiation by APETALA1.” Science 328 (5974): 85–89. PubMed
- Landt SG, Marinov GK, Kundaje A, Kheradpour P, Pauli F, Batzoglou S, Bernstein BE, Bickel P, Brown JB, Cayting P, et al (2012) ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia. Genome Res 22: 1813–1831. PubMed
- Lun ATL, Smyth GK (2014) De novo detection of differentially bound regions for ChIP-seq data using peaks and windows: controlling error rates correctly. Nucleic Acids Res 42: e95. PubMed
- Muiño JM, Kaufmann K, van Ham RC, Angenent GC, Krajewski P (2011) ChIP-seq Analysis in R (CSAR): An R package for the statistical detection of protein-bound genomic regions. Plant Methods 7: 11. PubMed
- Wilbanks EG, Facciotti MT (2010) Evaluation of algorithm performance in ChIP-seq peak detection. PLoS One. doi: 10.1371/journal.pone.0011471. PubMed
- Zhang Y, Liu T, Meyer CA, Eeckhoute J, Johnson DS, Bernstein BE, Nussbaum C, Myers RM, Brown M, Li W, et al (2008) Model-based analysis of ChIP-Seq (MACS). Genome Biol. doi: 10.1186/gb-2008-9-9-r137. PubMed
Last modified 2022-05-25: some edits (51627e9bf)