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jxtx / GLBio_3D.md
Last active May 17, 2017 22:05
Notes for 3D genome track at GLBio 2017

Keles -- Statistical Methods for profiling long range chromatin interactions from repetitive regions of the genome

  • Multi-mapping reads (multi-reads) are typically thrown out in many HTS analyses incuding Hi-C
    • Assays predominently rely on short-read (50-150bp) so multi-reads are common
    • Using ChIP-seq as an example, incorporating multi-reads finds peaks in regions where "uni-reads" do not
    • e.g. Perm-seq using DHS + ChIP-seq data and multi-reads. 27.3% more peaks compared to ENCODE uniform processing pipeline
  • How to combine this with Hi-C data?
    • Hi-C read processing
      • Typical pipelines: singletons, multi-mapping ends, low map quality, and unaligned all discarded
  • Evaluation of the impact of this using IMR90 and Plasmodium datasets