dbfinder2015

Transcript

1. dbFinder
   Leonardo Collado-Torres
   November 30, 2015
   

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2. DER finder approach
   • Find contiguous base pairs with
   Differential Expression signal à DE
   Regions or DERs
   • Find nearest annotated feature
   

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3. coverage
   vector
   2 6 0 11 6
   Genome
   (DNA)
   Read coverage
   Adapted from @jtleek
   

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4. Jaffe et al, Nat. Neuroscience, 2015
   

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5. Single-base F-statistics
   • Null model
   • Alternative Model
   • F-statistic
   i: base-pair
   j: sample
   Collado-Torres et al, bioRxiv, 2015
   

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6. Single-base F-statistics
   Collado-Torres et al, bioRxiv, 2015
   BrainSpan data
   

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7. Compare DERs vs annotation
   Collado-Torres et al, bioRxiv, 2015
   BrainSpan data
   

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8. Common ChIP-seq analysis pipeline
   Peak Call
   Peak Call
   Peak Call
   Peak Call
   Peak Call
   Peak Call
   …
   Sample 1
   Sample 2
   Sample 3
   Sample N
   Sample N-1
   Sample N-2
   2100
   4230
   7654
   1236
   5400
   5954
   # Unique
   Peaks
   Merge*
   All Unique
   Peaks
   (40000)
   ir
   Identify which merged
   peaks are differentially
   expressed using coverage
   (40000 tests)
   

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9. Common ChIP-seq analysis pipeline
   Peak Call
   Peak Call
   Peak Call
   Peak Call
   Peak Call
   Peak Call
   …
   Sample 1
   Sample 2
   Sample 3
   Sample N
   Sample N-1
   Sample N-2
   2100
   4230
   7654
   1236
   5400
   5954
   # Unique
   Peaks
   Merge*
   All Unique
   Peaks
   (40000)
   ir
   Identify which merged
   peaks are differentially
   expressed using coverage
   (40000 tests)
   Biological variability within a
   group is not incorporated into
   finding peaks
   Variability across
   peaks is not formally
   incorporated into
   merging step
   

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10. Base-resolution differential binding
    ChIP-seq analysis pipeline
    …
    Sample 1
    Sample 2
    Sample 3
    Sample N
    Sample N-1
    Sample N-2
    Identify differentially
    bound peaks using
    single base-level
    derfinder analysis
    Single List of
    Candidate
    Peaks
    Empirical p-values
    via permutations and
    FDRs
    Significant
    Peaks for
    Differential
    Binding
    “dbFinder”
    

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11. Re-analysis of H3K4me3 data from
    developing and aging human brain
    • Downloaded H3K4me3 data: NeuN+ fraction
    of postnatal frontal cortex samples (Shuhla et
    al, PLoS Genetics 2013)
    • Modeled linear age-related changes in
    coverage across the genome
    • Identified 561 dbPeaks at FDR < 10% (using
    100 permutations, 2.5 hours on JHPCE)
    

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12. Re-analysis of H3K4me3 data from
    developing and aging human brain
    

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13. Re-analysis of H3K4me3 data from
    developing and aging human brain
    Post-hoc analysis on mean coverage per sample per dbPeak
    

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14. Re-analysis of H3K4me3 data from
    developing and aging human brain
    Overlap with published 1157 peaks (742
    decrease across age, 415 increase):
    Down Up
    Not in dbPeaks 605 397
    In dbPeaks 137 18
    Down Up
    In Publish Peaks 278 21
    Not Publish Peaks 262
    Published peaks
    overlapping
    significant dbPeaks
    Significant dbPeaks
    overlapping
    published peaks
    

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15. Re-analysis of H3K4me3 data from
    developing and aging human brain
    • Much shorter peaks in dbFinder analysis:
    median of 104bp (IQR: 87-132) versus 2047bp
    (1490-2959) in published peaks
    

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16. Future directions
    • Add smoothing to test statistics prior to
    dbPeak finding
    • Analyze other datasets:
    – differentially binding by tissue/cell type from
    ENCODE across multiple groups
    

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17. Acknowledgements
    Hopkins
    Jeffrey Leek
    LIBD
    Andrew Jaffe
    Indigo Rose
    Funding
    NIH
    LIBD
    CONACyT México
    

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