Omics Year 1 Report by Bing Ren

Achievements

• Common experiment protocol
• Data file formats

Goals for Year 2

• Data standards for Hi-C and ChIA-PET
• Quality metric for chromatin organization features

Main challenges and obstacles for OMICS group

• Gold standards for chromatin features
• Definition for “reference 4D genome” (probably a reference sweep list for terms and etc. rather than a detailed “reference genome”

Build consensus in common terminology

Data standards for Hi-C:

• Needed when external experimental groups submit their own Hi-C data
• The data standards should reflect what types of feature the datasets are trying to resolve because different features will require vastly different levels of resolution (low for compartment/domains but high for loops)
  • Do we need to enforce a minimum sequencing depth for Hi-C data? ENCODE has a requirement of 20M reads for phase II and 40M for phase III to ensure the number of binding sites (peaks) does not appear limited.
  • Datasets may be divided into two (or more) categories by resolution.
• Data will have a large amount of heterogeneity
• Standard libraries can provide a good “sanity test” for newly generated data for better aggregation analysis
• Categorize quality control libraries
  • Do groups do their internal controls individually or mandate a QC standard for all datasets

Determine the minimum numbers of reads required for datasets

• Distinct reads appears to be also very important because it is possible to have lots of reads but a very low molecular complexity, leading to waste of reads
• Reproducibility analysis
• However, saturation analysis by Erez group showed that there may be less benefit once the number of unique reads reaches certain level. (~2B-3B contacts, i.e. read pairs in the library assuming a high quality library)
• Inter-chromosomal and intra-chromosomal data may need to be separately considered because the underlying biological process.
• Define a minimal standard with the minimal read counts, read depths and quality control of the libraries.
• Early standard pushout may be more beneficial (can be raised later on) so that people don’t have to regenerate data once a standard is implemented in the future for the “reference genome”.