Using Data Science to Study Human Brain Genomic Measurements Leonardo Collado-Torres @fellgernon

Mo#va#ng problem: iden#fy and validate regions of the genome that change expression during brain development

Research theme - annota#on-agnos#c - reproducible analyses - easily accessible data - sta#s#cal tools for the genomics community

RNA-seq reads Genome (DNA) RNA transcripts (many possible variants) Measuring gene expression: RNA-seq Adapted from @jtleek

Genome (DNA) Mapped reads Adapted from @jtleek Common analysis pipelines: • Feature coun#ng (gene or exon level) • Transcript assembly

Challenges in counting hBp://www-huber.embl.de/users/anders/HTSeq/doc/count.html

Annotation variation Frazee et al, Biostatistics, 2014

Project size is increasing ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 2009 (11) 2010 (46) 2011 (121) 2012 (235) 2013 (408) 2014 (625) 2015 (548) 2016 (18) 7 8 9 10 11 12 Project size in base−pairs over the years log10 base−pairs per project hBps://jhubiosta#s#cs.shinyapps.io/recount/

Genome (DNA) Mapped reads Adapted from @jtleek

DER finder approach •  Find con#guous base pairs with Differen#al Expression signal à DE Regions or DERs •  Find nearest annotated feature

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

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Identifying brain development DERs Fetal Infant Child Teen Adult 50+ 6 / group, N = 36 Discovery data Null: Alt: Models Initial results Jaffe et al, Nat. Neuroscience, 2015 50,650 DERs replicated 63,135 DERs Final results

Jaffe et al, Nat. Neuroscience, 2015

Widespread differential expression of novel transcriptional activity Jaffe et al, Nat. Neuroscience, 2015

Age-associated DERs lack regional specificity in the human brain BrainSpan data Jaffe et al, Nat. Neuroscience, 2015

Propor#on 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

Chromatin immunoprecipitation seq. http://assets.illumina.com/content/dam/illumina-marketing/images/techniques/large/web-graphic-chipseq-workflow-large.jpg

Common ChIP-seq analysis pipeline Sample 1 Sample 2 ... Sample N 1 call peaks call peaks call peaks U 11 U 12 U 1N Number of unique peaks Merge unique peaks Total peaks: U merged ≤ U 1 + U 2 Determine differentially bound peaks between groups 1 & 2 Total tests: U merged 1 Total: U 1 Sample 1 Sample 2 ... Sample N 2 call peaks call peaks call peaks U 21 U 22 U 2N Number of unique peaks 2 Total: U 2 Group 1 Group 2 (A) (A) (B) (C)

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Brain ChIP-seq data EpiMap project

Variation mostly explained ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 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● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 20 40 60 80 100 Percentage variance explained Brain region C ell type Age at death H em isphere PM I pH Sex H eight BM I C hrom atin am ount M apped reads Individual Flow cell batch Library batch R esidual variation All Regions H3K4me3 data: all regions with binding signal

Differentially bound regions 0 16 64 128 256 512 A:N−:− A:N+:− A:N−:+ A:N+:+ D:N−:− D:N+:− D:N−:+ D:N+:+ Coverage PRB2, 0 bp from tss: overlaps 5' − + Genes 11652500 11653000 11653500 11654000 11654500 − Tx chr12

Collado-Torres et al, F1000Research, 2015 regionReport chr start end strand p-value chr1 1000 2000 + 0.9 chr2 5000 8000 - 0.001 chr3 2468 2668 + 0.051 . . . . . . . . . . . . . . . chrX 6000 6300 + 0.009 chrX 6500 6800 - 0.5 Genomic workflow: identify regions renderReport (A) default (B) custom (C) derfinderReport (D) DESeq2Report (E) edgeReport Create HTML/PDF report

Collado-Torres et al, F1000Research, 2015 regionReport

Collado-Torres et al, F1000Research, 2015 Interactive HTML reports (A) (B) Clickable buttons: show/hide code

Collado-Torres et al, F1000Research, 2015 Interactive HTML reports (A) (B)

•  Resource with data from 2,040 projects •  Aligned with •  Total RNA-seq samples: 49,657 + 9,662 = 59,319 hBps://jhubiosta#s#cs.shinyapps.io/recount/

recount: via the web hBps://jhubiosta#s#cs.shinyapps.io/recount/

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Mo#va#ng problem: iden#fy and validate regions of the genome that change expression during brain development 1. derfinder permits discovery of novel expressed & differen#ally bound regions 2.  we iden#fied & validated gene expression changes in the developing brain 3.  we have developed tools for reproducible shareable repor#ng 4.  these tools can be easily be used to process 2,040 projects via recount

Acknowledgements Advisors Jeffrey Leek Andrew Jaffe Collaborators Alyssa Frazee Abhinav Nellore Michael Love Ben Langmead Rafael Irizarry EpiMap project Funding NIH LIBD JHU-Biostats CONACyT México Conference Support Harvard Health Policy Data Science Lab, SACNAS 2016

References + software + code: @fellgernon •  Collado-Torres, et al. Nucleic Acids Research (2016) doi: 10.1093/nar/gkw852 –  http://bioconductor.org/packages/derfinder –  http://leekgroup.github.io/derSupplement/ •  Collado-Torres, et al. F1000Research (2015) doi:10.12688/f1000research.6379.1 -  http://www.bioconductor.org/packages/regionReport -  http://leekgroup.github.io/regionReportSupp/ •  Collado-Torres and Nellore, et al. bioRxiv (2016) doi: 10.1101/068478 –  http://bioconductor.org/packages/recount –  https://jhubiostatistics.shinyapps.io/recount •  Nellore, Collado-Torres, et al. Bioinformatics (2016) doi:10.1093/bioinformatics/btw575 -  rail.bio • Nellore, …, Collado-Torres, et al. bioRxiv (2016) doi:10.1101/038224 - intropolis.rail.bio •  Jaffe, Shin, Collado-Torres, et al. Nat. Neurosci. (2015) doi:10.1038/nn.3898 –  https://github.com/lcolladotor/libd_n36 –  https://github.com/leekgroup/enrichedRanges