Upgrade to Pro — share decks privately, control downloads, hide ads and more …

Dong X. et. al. "Modeling gene expression using chromatin features in various cellular contexts"

Itoshi NIKAIDO
September 28, 2012

Dong X. et. al. "Modeling gene expression using chromatin features in various cellular contexts"

2012/09/29 ENCODE 勉強会

Itoshi NIKAIDO

September 28, 2012
Tweet

More Decks by Itoshi NIKAIDO

Other Decks in Science

Transcript

  1. Dong X et. al. Modeling gene
    expression using chromatin features in
    various cellular contexts
    2012/09/29 ENCODE ษڧձ
    ೋ֊ಊѪ / @dritoshi #encodejp-28
    ཧԽֶݚڀॴ ൃੜɾ࠶ੜՊֶ૯߹ݚڀηϯλʔ

    View Slide

  2. ͜ͷࢿྉͷ࠷৽൛ͷҎԼʹ͋Γ·͢
    http://cat.hackingisbelieving.org/lecture/
    ͜ͷϑΝΠϧ͸ ΫϦΤΠςΟϒɾίϞϯζ දࣔ 2.0 Ұൠ ϥΠηϯεͷԼʹఏڙ͞Ε͍ͯ·͢ɻ
    http://genomebiology.com/content/13/9/R53
    “catway dritoshi” Ͱݕࡧ

    View Slide

  3. Chromatin features ͔ΒҨ఻ࢠൃݱ͕༧ଌͰ͖Δ͔?
    4ͭͷ໰͍
    1. Can we reproduce the quantitative relationship between
    gene expression levels and histone modifications?
    2. Does the relationship hold across different human cell lines
    and between different groups of genes?
    3. Do the most predictive chromatin features differ depending
    on the expression quantification technique used?
    4. How well can the chromatin features predict expression
    levels of RNA from different cell compartments and/or RNA
    extracted by different

    View Slide

  4. Chromatin features ͕సࣸΛ੍ޚ͢Δ
    Ҩ఻ࢠपลͷώετϯम০, ΫϩϚνϯߏ଄ʹΑΔస੍ࣸޚ
    7 histone modifications
    1 histone variant
    DNase I hypersensitivity in 7 cell
    Cause = Chromatin feature
    RNA-seq
    RNA-PET
    deepCAGE
    Effect = transcription
    Cause = Chromatin feature
    Effect = transcription

    View Slide

  5. Chromatin featuresͷσʔλΛදݱ
    Ҩ఻ࢠपลͷώετϯम০, ΫϩϚνϯߏ଄ͷϕΫτϧΛ࡞Δ

    View Slide

  6. RNAసࣸྔσʔλͷදݱ
    స͕ࣸON/OFFͷҨ఻ࢠʹ෼͚ͯ͠·͏
    Random forests ͰON/OFFͷ2܈ʹ෼ྨ͢Δ

    View Slide

  7. ϞσϧԽ͢Δ
    ճؼϞσϧ
    1. Linear regression
    2. multivariate adaptive regression splines (MARS)
    3. Random forests

    View Slide

  8. ϞσϧΛ౷߹͢Δ
    ෼ྨ*ճؼϞσϧ

    View Slide

  9. ϞσϧΛධՁ͢Δ
    ༧ଌͱ࣮ଌΛൺֱ͢Δ

    View Slide

  10. ༧ଌੑೳ1
    ༧ଌͱ࣮ଌΛൺֱ͢Δ

    View Slide

  11. ༧ଌੑೳ2
    ༧ଌͱ࣮ଌΛൺֱ͢Δ

    View Slide

  12. ·ͱΊ1
    chromatin features ͔Βసࣸྔ͕ྑ͘༧ଌͰ͖Δ
    0. chromatin features ͷసࣸ΁ͷӨڹΛఆྔతʹධՁͰ͖ͨ
    ൃݱON/OFF: H3K9ac > H3K4me3 > DNase I > H3K4me2 ...
    సࣸྔ: H3K79me2 > H3K36me3 > DNase I > H3K9ac ...
    1. 2ஈ֊ͷ༧ଌํ๏ΛఏҊ
    ON/OFFͷ෼ྨͱճؼϞσϧ

    View Slide

  13. ·ͱΊ2
    ΄͔ʹٞ࿦͞Ε͍ͯΔ͜ͱ
    1. Nucleus, Cytosol, Whole Cell ༝དྷͷRNAྔΛ༧ଌͰ͖Δ͔?
    Ͱ͖ΔɻCytosol > Whole Cell >> Nucleus
    2. RNA-seq, CAGE, RNA-PETͷͲΕ͕chromatin featuresͱͷ૬
    ͕ؔߴ͍͔?
    CAGE > RNA-PET = RNA-seq
    3. ΄͔ͷࡉ๔ͷసࣸྔΛઆ໌Ͱ͖Δ͔?
    R = 0.8 ఔ౓Ͱ
    4. CpGͱͷؔ࿈͸?
    High CpG ͷ΄͏͕༧ଌ͕Α͍

    View Slide

  14. ͜͏ߟ͑Δ
    Α͔ͬͨ͜ͱͱ࢒͞Εͨ՝୊
    Α͔ͬͨ͜ͱ
    1. ༧ଌͰ͖ͨͷ͸Α͔ͬͨͶ
    2. chromatin features ͷͦΕͧΕͷॏཁੑ͕Θ͔ͬͨͷ͸Α͔
    ͬͨ
    ՝୊
    1. bestbin Λ૬ؔͰऔ͍ͬͯΔͷ͸͍͍ͷ͔ͳ?
    2. ౷ܭϞσϧͰ͍͍ͷ͔ͳ? Ϟϊͷಈ͖͕Θ͔Βͳ͍
    3. CAGE, RNA-seq, RNA-PET͕ൺֱͰ͖Δ΄ͲϑΣΞ?
    4. Ҩ఻ࢠʹண໨ͨٞ͠࿦΋ཉ͍͠ΑͶ
    5. ༧ଌ݁Ռ͔ΒసࣸΛσβΠϯͰ͖Δͷ͔?

    View Slide

  15. Software
    ෼ྨ΍ճؼͳͲ
    Calculation of the mean density of chromatin features
    bigWigSummary: BigWig and BigBed: enabling browsing of large
    distributed datasets
    Variable importance
    relaimpo: Relative importance of regressors in linear models
    Regression/classification
    randomForest: Breiman and Cutler's random forests for
    classification and regression
    Regression
    earth: Multivariate Adaptive Regression Spline Models

    View Slide

  16. ͜ͷࢿྉͷ࠷৽൛ͷҎԼʹ͋Γ·͢
    http://cat.hackingisbelieving.org/lecture/
    ͜ͷϑΝΠϧ͸ ΫϦΤΠςΟϒɾίϞϯζ දࣔ 2.0 Ұൠ ϥΠηϯεͷԼʹఏڙ͞Ε͍ͯ·͢ɻ
    http://genomebiology.com/content/13/9/R53
    “catway dritoshi” Ͱݕࡧ

    View Slide