Feng Lab - Data Science Toolbox and ChIP-Seq
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  • Getting started
  • For today
  • Examples from the Wild I: REGULAR EXPRESSIONS
  • Examples from the Wild 2: IPython Notebooks
  • Examples from the Wild 3: Git, Github, and Gists
  • Examples from the Wild 4: R, the Bioconductor Project for R, RStudio
  • Sources
  • Going forward
  • Literature Selections for ChIP-seq
  • ACRONYMS
Feng Lab - Data Science Toolbox and ChIP-Seq
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SourcesΒΆ

The sources for the information used today came from those linked throughout the content.

However, certain sources deserve special highlighting as they were particularly useful in developing this presentation, contain a wealth of related resources, or are especially pertinent at this stage.

  • Practical Computing for Biologists book by Haddock and Dunn
  • Interactive notebooks: Sharing the code by Helen Shen. Nature. 2014 Nov 6;515(7525):151-2. doi: 10.1038/515151a. PMID: 25373681
  • Programming tools: Adventures with R by Sylvia Tippmann. Nature. 2015 Jan 1;517(7532):109-10. doi: 10.1038/517109a. PMID: 25557714
  • Feng et al. 2012. Identifying ChIP-seq enrichment using MACS.Nat Protoc. 2012 Sep; 7(9): 10.1038/nprot.2012.101.
  • Titus Brown and Colleague’s Next-Gen Sequence Analysis Workshops, most recent is [Next-Gen Sequence Analysis Workshop (2014)(http://angus.readthedocs.org/en/2014/) Particularly pertinent are the sections Istvan Albert’s 2012 ChIP-Seq lecture, Day 7: ChIP-seq: Peak Predictions and Cis-regulatory Element Annotations, Using MEME to identify TF binding motif from ChIP-seq data and here.
  • ChIP- and DNase-seq data analysis workshop 2014
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© Copyright 2015, Wayne Decatur. Revision 747c2449.

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