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gbs2015

 gbs2015

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Leonardo Collado-Torres

October 22, 2015
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  1. Annotation-agnostic differential expression analysis Leonardo Collado-Torres @fellgernon

  2. motivating problem: identify and validate regions of the genome that

    change expression during brain development
  3. RNA-seq reads Genome (DNA) RNA transcripts (many possible variants) Measuring

    gene expression: RNA-seq Adapted from @jtleek
  4. Challenges in counting h"p://www-huber.embl.de/users/anders/HTSeq/doc/count.html

  5. Annotation variation Frazee et al, Biostatistics, 2014

  6. DER finder approach •  Find contiguous base pairs with Differential

    Expression signal à DE Regions or DERs •  Find nearest annotated feature
  7. coverage vector 2 6 0 11 6 Genome (DNA) Read

    coverage Adapted from @jtleek
  8. Jaffe et al, Nat. Neuroscience, 2015

  9. Single-base F-statistics •  Null model •  Alternative Model •  F-statistic

    i: base-pair j: sample Collado-Torres et al, bioRxiv, 2015
  10. Single-base F-statistics Collado-Torres et al, bioRxiv, 2015 BrainSpan data

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

    data
  12. Input data n samples → ~348 million nt 11.24% coverage

    Rows with at least 1 sample with coverage > 5 Adapted from @jtleek
  13. Finding DERs by expressed-regions

  14. Simulation similar in power, yet allows new discoveries

  15. Identifying brain development DERs Fetal Infant Child Teen Adult 50+

    6 / group, N = 36 Discovery data Null: Alt: Models Cutoff Details •  Rank DERs by area •  1000 permutations •  Control FWER (≤ 5%) by max area per permutation Results 63,135 DERs 20.509 Corresponds to p-value 10-08 Jaffe et al, Nat. Neuroscience, 2015
  16. Replicating DERs Fetal Infant Child Teen Adult 50+ 6 /

    group, N = 36 Replication data Null: Alt: Models Cutoff Details Per sample and per DER calculate average expression Results 50,650 DERs replicated Single F-statistic per DER p-value < 0.05 Jaffe et al, Nat. Neuroscience, 2015
  17. Jaffe et al, Nat. Neuroscience, 2015

  18. Widespread differential expression of novel transcriptional activity Jaffe et al,

    Nat. Neuroscience, 2015
  19. DERs validate: Cytosolic vs total mRNA fractions Jaffe et al,

    Nat. Neuroscience, 2015
  20. CBC: 28 MD: 24 STR: 28 AMY: 31 HIP: 32

    DFC: 34 Total N samples: 487 BrainSpan data Coverage Data from BrainSpan: h"p://download.alleninsUtute.org/brainspan/MRF_BigWig_Gencode_v10/ VFC: 30 MFC: 32 OFC: 30 M1C: 25 S1C: 26 IPC: 33 A1C: 30 STC: 35 ITC: 33 V1C: 33
  21. Age-associated DERs lack regional specificity in the human brain BrainSpan

    data Jaffe et al, Nat. Neuroscience, 2015
  22. ProporUon of Cells Expression changes across development may represent a

    changing neuronal phenotype Jaffe et al, Nat. Neuroscience, 2015 Estimation method: Houseman et al, BMC Bioinformatics, 2012
  23. LIBD Human DLPFC Development •  UCSC “Track Hub” Jaffe et

    al, Nat. Neuroscience, 2015
  24. • Data: 3 tissues, 12 samples each • Align with • Identify expressed

    regions with derfinder – Adjust coverage (40 mi) – Find expressed regions (cutoff 5) – Discard ERs < 9 bp GTEX: expressed regions
  25. •  221246 ERs – 160817 strictly exonic (73%) – 26740 exonic +

    intronic (12%) – 22375 strictly intronic (10%) •  Can strictly intronic ERs differentiate tissues? Presence of intronic ERs
  26. PCs differentiate tissues

  27. PCs differentiate tissues

  28. Differential intronic ERs adjusting for exonic ERs

  29. Differential intronic ERs | exonic ERs

  30. Differential intronic ERs | exonic ERs

  31. Collado-Torres et al, F1000Research, 2015 regionReport

  32. motivating problem: identify and validate regions of the genome that

    change expression during brain development 1. derfinder permits discovery of novel expressed regions 2. we identified & validated gene expression changes in the developing brain 3. we have developed tools for reproducible/shareable reporting
  33. Acknowledgements Hopkins Jeffrey Leek Alyssa Frazee Abhinav Nellore Ben Langmead

    LIBD Andrew Jaffe Jooheon Shin Nikolay Ivanov Amy Deep Ran Tao Yankai Jia Thomas Hyde Joel Kleinman Daniel Weinberger Harvard Rafael Irizarry Michael Love Funding NIH LIBD CONACyT México
  34. References + software + code •  Collado-Torres L, et al.

    bioRxiv (2015) doi:10.1101/015370 –  http://bioconductor.org/packages/derfinder •  Collado-Torres L, et al. F1000Research (2015) doi:10.12688/f1000research.6379.1 -  http://www.bioconductor.org/packages/regionReport -  http://lcolladotor.github.io/regionReportSupp/ •  Nellore, et al. bioRxiv (2015) doi:10.1101/019067 - rail.bio •  Jaffe AE, et al. Nat. Neurosci. (2015) doi:10.1038/nn.3898 –  https://github.com/lcolladotor/libd_n36 –  https://github.com/lcolladotor/enrichedRanges •  Frazee AC, et al. Biostatistics. (2014) doi:10.1093/biostatistics/kxt053 –  https://github.com/leekgroup/derfinder