liigh2019

11
Analyzing BrainSEQ Phase II and generating the
recount-brain resource
Leonardo Collado-Torres
Staff Scientist II
@fellgernon
Data Science I with Andrew Jaffe

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Questions I’ll answer today
• Who am I?
• What is the BrainSeq Phase II project?
• What is the recount-brain resource?

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What defines me
• Bioinformatics
• R and Bioconductor
• Reproducibility and best practices
• Outreach and community building
• Back in 2005 at @LCGUNAM:
I like math and coding; biology provides the challenging problems

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History
2005-2009
Undergrad in
Genomic Sciences
2009-2011 2011-2016 August 2016+
Data Science
Division Leader
!
!
PIs:
• Jeff Leek: 2012+
• Andrew Jaffe: 2013+
Ph.D. Biostatistics Staff Scientist I → II
Data Science Team I
PI: Andrew Jaffe

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2008+
• BioC 2008-2011, 2014, 2017
• useR!2013
• rOpenSci unconf 2018
• RStudio::conf 2019
@fellgernon
2010+
Interests
!
@LIBDrstats
2018+
@CDSBMexico
2018+
Defunct: BmoreBiostats, Biostats Cultural Mixers
Guest
@RLadiesBmore
Blog: http://lcolladotor.github.io
2011+
FB: 75k, Tw: 66k
weekly

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Software tools I use every day
Mercurial/git user 2009+
https://github.com/lcolladotor
From: Feb 21, 2019
Communication tool for work and communities

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My path to LIBD
2005-2009
Undergrad in
Genomic Sciences
2009-2011 2011-2016 August 2016+
Data Science
Division Leader
!
!
PIs:
• Jeff Leek: 2012+
• Andrew Jaffe: 2013+
Ph.D. Biostatistics Staff Scientist
Data Science Team I
Microarrays,
little RNA-seq
N = 12
(bacteria)
N = 59
N = 72
potential for 1,000
BSP2: N = 900
+ many more

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Ph.D. overview
The goal was to develop statistical methods and software [...] in
RNA-seq […]. We applied these methods to further our
understanding of neuropsychiatric disorders using the Lieber Institute
for Brain Development human brains collection (> 1000 samples).

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Lieber Institute for Brain Development
• Role: Staff Scientist II
• PI: Andrew Jaffe
Team:
• Staff Scientist: Emily Burke
• Research Associate: Madhavi Tippani
• Grad students: Matt Nguyen, Brianna Barry,
Kira Perzel Mandell
• Research Assistant: Nick Eagles
• Recent Alumni: Amanda Price, Stephen Semick
• Close collaborators: Carrie Wright, Nina Rajpurohit
• Role details: like a postdoc (major role in some projects) with some support projects
Lab at Amy Peterson’s MPH capstone presentation
amy-peterson.github.io

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Papers since 2016

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Papers since 2016
RNA-seq
WGBS
Biostatistics
RNA-seq
> 70,000 samples

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Lieber Institute for Brain Development
• DNAm on WGBS across development & cell types biorxiv.org/content/early/2018/09/29/428391
• RNA-seq from stem cells biorxiv.org/content/early/2018/07/31/380758
Peer reviewed:
• RNA-seq DE in Schizophrenia disorder & 2 brain regions doi.org/10.1016/j.neuron.2019.05.013
• miRNA kit prep comparison doi.org/10.1186/s12864
• DNAm and gene DE in Alzheimer’s disease doi.org/10.1007/s00401-019-01966-5
• RNA-seq smoking during pregnancy doi.org/10.1038/s41380-018-0223-1
• RNA-seq DE in Schizophrenia disorder on DLPFC doi.org/10.1038/s41593-018-0197-y
• Histamine signaling in autism spectrum disorder doi.org/10.1038/tp.2017.87
Pre-prints:

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Today
BrainSeq Phase II
brain

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BrainSeq: A Human Brain Genomics Consortium
DLPFC
495
samples
BrainSeq Phase I
polyA+
Jaffe et al., Nature Neuroscience, 2018
DLPFC
453
samples
HIPPO
447
samples
BrainSeq Phase II
RiboZero
THE SCIENTIFIC FRONTIER
Neuron, 2015
Collado-Torres et al, bioRxiv, 2018 → Neuron, 2019

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DATA
16
BrainSeq Phase II RNA-seq samples
DLPFC HIPPO total
adult (age >= 18) 374 370 744
prenatal 29 28 57
0 <= age < 18 50 49 99
total 453 447 900
• Non-psychiatric control and schizophrenia affected individuals
• Two brain regions: dorsolateral prefrontal cortex and hippocampus
All
samples

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DATA
17
BrainSeq Phase II RNA-seq samples: by case status
DLPFC HIPPO total
adult 222 238 460
prenatal 29 28 57
0 <= age < 18 49 48 97
total 300 314 614
DLPFC HIPPO total
adult 152 132 284
prenatal 0 0 0
0 <= age < 18 1 1 2
total 153 133 286
Control
Schizophrenia
cases

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DATA ANALYSIS
18
Focus on being conservative
1.Use well established processing methods
2.Apply strict expression cutoffs
3.Use replication when possible
4.Adjust for RNA quality degradation confounding
• Using the qSVA method
5.Avoid potential batch effects
• Drop problematic samples
6.Take into account correlation at the individual level

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RNA-SEQ APPROACH
19
BrainSeq Phase II
Pre-natal
Adult
ACTG
Birth
Unaffected
Controls
Patients with
Schizophrenia
RNA Sequencing
Genotyping
+ +
+
Gene Exons Expressed Regions
Transcripts Junctions
Age
CC CA AA
SZ CONT
DLPFC
HIPPO
+ region differences
For public data, check recount2

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DATA ANALYSIS
20
Main processing steps
1. Quality check (QC) on raw reads (FastQC)
2. Failed QC? Then trim reads (Trimmomatic)
3. Align reads to the genome (HISAT2)
4. Count features (featureCounts + others)
5. Calculate coverage (bam2wig)
6. Quantify transcripts (Salmon)
7. Create count tables (R)
8. Genotype samples (samtools + vcftools)
Emily E. Burke
Nextflow version in
preparation with
Winter Genomics
and Nick Eagles

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DATA ANALYSIS
21
Filter features with low expression
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0.0 0.2 0.4 0.6 0.8 1.0
20000 30000 40000 50000
mean expression cutoff
Number of features > cutoff
Feature Cutoff Unit
Gene 0.25 RPKM
Exon 0.30 RPKM
Jxn 0.46 RP10M
Tx 0.38 TPM
Gene
• Used mean across all 900 samples
• All analyses with filtered data
Mean
RPKM
# genes >
cutoff
Based on the segmented R package:
break-point estimation
jaffelab::expression_cutoff()

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DATA ANALYSIS
22
Differential expression models
• Region-specific for adult or fetal ages
• Using only adult samples or only prenatal samples
• Test for differences between DLFPC and HIPPO
• Development
• Linear age splines with breakpoints at developmental stages
• Test for interaction between age and brain region at these splines
• Case-control
• By brain region
• Test for differences between non-psychiatric controls and individuals with
schizophrenia
• For the first two models, we account for the fact that an individual can have two
correlated samples: one for each brain region
limma::duplicateCorrelation()

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DATA ANALYSIS
23
Differential expression models
• Region-specific for adult or prenatal ages
• Alternative: !"#$ = &' + )*+ + ,+" +
∑./0
1 23#45. + 6789:)8+ + 898);<227*3+=>+3+ + :?@ + :+*793
• Development
• Alternative: !"#$ = &' + )*+ ∗ :+*793 + B+8); ∗ :+*793 +
C7$8ℎ ∗ :+*793 + 73B)38 ∗ :+*793 + Eℎ7;= ∗ :+*793 +
8++3 ∗ :+*793 + )=F;8 ∗ :+*793 + ,+" +
∑./0
1 23#45. + 6789:)8+ + 898);<227*3+=>+3+ + :?@ + :+*793
• Case-control
• Alternative: !"#$ = &' + )*+ + ,+" + 6789:)8+ +
$:@∑./0
1 23#45. + 898);<227*3+=>+3+ + :?@ + $+*793,#+E7B7EK,L2 + M7)*39272

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DATA ANALYSIS
24
Using BrainSpan for replication: region-specific model
• P-value < 0.05 in BrainSpan, consistent direction
Similar results for the development model
prenatal adult
gene exon jxn
p<0.05
p<0.01
p<0.001
p<1e−04
p<1e−05
p<1e−06
p<0.05
p<0.01
p<0.001
p<1e−04
p<1e−05
p<1e−06
0.00
0.25
0.50
0.75
1.00
0.00
0.25
0.50
0.75
1.00
0.00
0.25
0.50
0.75
1.00
p−value threshold
Replication rate

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DATA ANALYSIS
25
Region-specific by age results
• For adults: 1,612 DE genes with Bonferroni < 0.01 that replicate in BrainSpan
• For prenatal samples: 32 DE genes
23
6
2
0
3
0
3
gene exon
jxn
DE features grouped by gene id (prenatal)
328
422
778
23
839
647
388
gene exon
jxn
DE features grouped by gene id (adult)

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DATA ANALYSIS
26
Region-specific by age results: adult enriched biological processes by region
G: gene, E: exon, J: exon-exon junction
D: DLPFC, H: HIPPO
cell−matrix adhesion
extracellular matrix organization
ameboidal−type cell migration
microtubule bundle formation
axoneme assembly
cilium movement
establishment of synaptic vesicle localization
synaptic vesicle transport
synaptic vesicle localization
signal release from synapse
neurotransmitter secretion
presynaptic process involved in chemical synaptic transmission
positive regulation of GTPase activity
regulation of GTPase activity
synaptic vesicle exocytosis
neurotransmitter transport
regulation of calcium ion−dependent exocytosis
synaptic vesicle cycle
regulation of synapse organization
positive regulation of synaptic transmission
regulation of neuron projection development
regulation of small GTPase mediated signal transduction
extracellular structure organization
positive regulation of nervous system development
positive regulation of neurogenesis
positive regulation of cell development
axon development
axonogenesis
regulation of hormone levels
cardiac chamber development
cardiac septum development
kidney epithelium development
nephron development
urogenital system development
cardiac chamber morphogenesis
cardiac septum morphogenesis
renal system development
kidney development
regulation of transmembrane transport
actomyosin structure organization
regulation of trans−synaptic signaling
modulation of chemical synaptic transmission
synapse organization
regulation of cell morphogenesis
synaptic transmission, glutamatergic
regulation of synaptic transmission, glutamatergic
potassium ion transmembrane transport
cellular potassium ion transport
potassium ion transport
G.D
(609)
G.H
(573)
E.D
(1101)
E.H
(1087)
J.D
(850)
J.H
(823)
GeneRatio
0.02
0.03
0.04
0.05
0.06
0.01
0.02
0.03
0.04
p.adjust
ontology: BP

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DATA ANALYSIS
27
Development model: similar composition in prenatal across regions by RNA fraction
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FQN Neurons Oligodendrocytes
Prenatal
Infant
C
hild
Teen
Adult
50+
Prenatal
Infant
C
hild
Teen
Adult
50+
Prenatal
Infant
C
hild
Teen
Adult
50+
0.0
0.2
0.4
0.0
0.2
0.4
0.6
0.0
0.2
0.4
0.6
Cell Type Proportion
Region
DLPFC
HIPPO

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Pluripotency Glial
Fetal
Infant
C
hild
Teens
Adult
50+
Fetal
Infant
C
hild
Teens
Adult
50+
0.4
0.6
0.8
0.0
0.1
0.2
0.3
Age Group
Cell Type Proportion
Region
DLPFC
Hippo
DATA ANALYSIS
28
Development model: similar composition in prenatal across regions by DNAm
Stephen A. Semick

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DATA ANALYSIS
29
Development model results
• 5,982 (~55%) genes contain differentially expressed exons and splice junctions that
replicated in BrainSpan (Bonferroni < 1%)
2354
2260
1762
243
5982
8501
1558
gene exon
jxn
DE features grouped by gene id

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DATA ANALYSIS
30
• Normalized expression over age for GABRD
−2 0 2 4 6
log2(CPM + 0.5)
14 16 18 20 22
PCW
0.0 0.2 0.4 2 4 6 8 12 14 16 18 2020 30 40 50 50 55 60 65 70 75 80 85
ENSG00000187730.7 GABRD p−bonf 0
Age
DLPFC HIPPO

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DATA ANALYSIS
31
• Normalized expression over age after removing effect of terms from the null model
jaffelab::cleaningY() and jaffelab::agePlotter()
−2 −1 0 1 2 3
log2(CPM + 0.5) − covariate effects removed
14 16 18 20 22
PCW
0.0 0.2 0.4 2 4 6 8 12 14 16 18 2020 30 40 50 50 55 60 65 70 75 80 85
ENSG00000187730.7 GABRD p−bonf 0
Age
DLPFC HIPPO

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qSVA WORKFLOW
32 Slide adapted from Amy Peterson
Jaffe et al., PNAS, 2017
Model 1 (6429 genes)
Log2 FC Dx
Log2 FC Degradation
http://research.libd.org/rstatsclub/2018/12/11/quality-surrogate-variable-analysis/

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DEqual HIPPO
33
Model 1 (6429 genes)
Model 1. Naïve model
E / = 10
+ 11
45
DEqual plots demonstrate effectiveness of statistical correction
r = 0.412
Slide adapted from Amy Peterson
Log2 FC Dx
Log2 FC Degradation
HIPPO
333
samples

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DEqual HIPPO
34
Model 1 (6429 genes) Model 2 (63 genes)
E / = 10 + 1145
Model 2. Added RNA-quality and demographic covariates
E / = 10 + 1145 + 12FGH + 13JH5+ 14LMNOPFNH+ 15RPSTRFte + 16GHVHPFNH
+ 17PXS + ∑Z[\
] γMJV_`aM
r = 0.412 r = 0.0712
Log2 FC Dx Log2 FC Dx, adj. cov
Log2 FC Degradation
Log2 FC Degradation
HIPPO
333
samples

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DEqual HIPPO
35
Model 1 (6429 genes) Model 2 (63 genes) Model 3 (48 genes)
E / = 10 + 1145
Model 2. Added RNA-quality and demographic covariates
+ 17PXS + ∑Z[\
] γMJV_`aM
Model 3. Added qSVs
+ 17PXS + ∑Z[\
] γMJV_`aM
+ ∑Z[\
d eMfghM
HIPPO
333
samples
r = 0.412 r = 0.0712 r = -0.00173
Log2 FC Dx Log2 FC Dx, adj. cov Log2 FC Dx, adj
qSVs
Log2 FC Degradation
Log2 FC Degradation
Log2 FC Degradation

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DATA ANALYSIS
36
Case-control: by region
• 48 DE genes at FDR <5% in hippocampus, 243 in DLPFC (FDR <5%)
−6 −4 −2 0 2 4
−6 −4 −2 0 2 4 6
t−statistic HIPPO
t−statistic DLPFC
r = 0.276
Amy Peterson
DLPFC FDR<10%, HIPPO FDR<20%

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DATA ANALYSIS
37
−6 −4 −2 0 2 4 6
−6 −4 −2 0 2 4 6
t−statistic DLPFC
t−statistic BSP1
r = 0.413

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axon development
axonogenesis
regulation of axonogenesis
regulation of neuron projection development
neutrophil chemotaxis
regulation of B cell proliferation
regulation of B cell activation
positive regulation of B cell activation
B cell receptor signaling pathway
B cell activation
lymphocyte activation
regulation of leukocyte cell−cell adhesion
regulation of cell−cell adhesion
positive regulation of alpha−beta T cell activation
regulation of leukocyte activation
positive regulation of lymphocyte activation
positive regulation of cell activation
positive regulation of leukocyte activation
leukocyte migration
positive regulation of leukocyte cell−cell adhesion
positive regulation of T cell activation
leukocyte chemotaxis
response to organophosphorus
ATF6−mediated unfolded protein response
positive regulation of cell adhesion
cell chemotaxis
positive regulation of cell−cell adhesion
protein folding
protein folding in endoplasmic reticulum
HgC
(137)
HeC
(306)
DgC
(297)
DeS
(250)
GeneRatio
0.025
0.050
0.075
0.100
0.01
0.02
0.03
0.04
p.adjust
ontology: BP
DATA ANALYSIS
38
• BP enrichment in Control > SCZD at gene level
• Immune processes
g: gene, e: exon, j: exon-exon junction
D: DLPFC, H: HIPPO, C: control, S: SCZD

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Gene Individual 1 Individual 2
1 10 15
2 5 22
…
DLPFC
Gene Individual 1 Individual 2
1 10 17
2 6 16
…
HIPPO
correlation( (10, 5, …), (10, 6, …) ) =~ 0.9
correlation( (15, 22, …), (17, 16, …) ) =~ 0.7
Individual 1
Individual 2
Control vs SCZD

View Slide

Gene: 0.0164
Exon: 0.0499
Jxn: 1.72 * 10-5
Tx: 0.00992
Control SCZD
0.54 0.55 0.56 0.57
cleaned expr (keeping Dx) − jxnRp10m
p−value: 1.72e−05
SCZD diagnosis
Correlation
Decreased coherence in SCZD

View Slide

DATA ANALYSIS
41
HIPPO eQTLs
• 11,237,357 eQTL associations (FDR <1%) across genes, exons and junctions
corresponding to 17,719 genes
Emily E. Burke
2061
3183
2163
274
5945
2915
1178
gene exon
jxn
eQTLs grouped by gene id
Includes 60 risk SNPs from PGC2
8
+,332
E
0 1 2
−1 0 1 2 3 4
chr2:5822204358229ï-[Q
rs74563533:58250433:G:A
r2:58 250 433
Residualized Expression
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0 1 2
−1 0 1 2 3 4
chr2:5822204358229ï-[Q
rs75575209:58138192:A:T
r2:58 138 192
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p=5.75e−34
p=3.82e−81
F

View Slide

DATA ANALYSIS
42
Region dependent eQTLs
• 205,618 region-dependent eQTLs (FDR <1%) corresponding to 1,484 genes
• Includes 3 PCG2 schizophrenia risk loci
Emily E. Burke
19394
10734
6493
2622
3937
4398
34259
gene exon
jxn
eQTLs grouped by SNP id
488
246
319
18
99
63
251
gene exon
jxn
eQTLs grouped by gene id

View Slide

DATA ANALYSIS Region dependent eQTLs
0.D 1.D 2.D 0.H 1.H 2.H
−1 0 1 2 3
Overlaps gene NRGN
chr11:124742693−124745500(+) (Jxn)
rs12293670:124612932:A:G
p=5.27e−26

View Slide

A B
0.D 1.D 2.D 0.H 1.H 2.H
4.0 4.4 4.8 5.2
LRP1(16(
(Exon)
rs324015
p=3.91e−05
0.D 1.D 2.D 0.H 1.H 2.H
−1 0 1 2 3
2YHUODSVJHQH15*1
FKUï-[Q
rs12293670:124612932:A:G
p=5.27e−26
C D
0.D 1.D 2.D 0.H 1.H 2.H
−1 0 1 2 3 4
2YHUODSVJHQH1*()
FKUïï-[Q
rs4144797:233562197:T:C
p=3.5e−14
0.D 1.D 2.D 0.H 1.H 2.H
6.8 7.2 7.6 8.0
LRP1
FKUï-[Q
rs324015
p=2.02e−06
D: DLPFC, H: HIPPO
DATA ANALYSIS
Region dependent eQTLs
These 3 SNPs are also
meQTLs (Jaffe et al, 2016)

View Slide

Overall eQTLs at FDR < 1% - rAggr eQTL analysis with PCG2 risk SNPs
Hippocampus DLPFC
# unique SNPs (unique index SNPs) 5510 (103) 6780 (116)
# unique features 1731 2525
# Unique genes 123 171
# Unique transcripts 244 332
# Unique exons 857 1363
# Unique junctions 507 659
Emily E. Burke
21 8
95
DLPFC HIPPO
In BSP2: 163/179 (91.1%)
FDR <1%: 124/163 (76.6%)

View Slide

• We will soon update our eQTL browser at http://eqtl.brainseq.org/ Bill Ulrich

View Slide

TWAS
Gusev et al, Nature Genetics, 2016

View Slide

TWAS
SNP ID chromosome position
rs101 12 1
rs102 13 10000
…
rs101:A:T 12 1
rs102 13 10005
…
rs101 12 1
rs102 13 10000
…
LD reference LIBD BSP2 SNPs
GWAS summary SNPs
https://github.com/LieberInstitute/brainseq_phase2/blob/master/twas/README.md
1,190,321 82,393,211
6,500,475
CLOZUK+PGC2

View Slide

TWAS
rs101:A:T 12 1
rs102 13 10005
…
rs101:A:T 12 1
rs102 13 10005
…
rs101:A:T 12 1
rs102 13 10005
…
LD reference LIBD BSP2 SNPs
GWAS summary SNPs
https://github.com/LieberInstitute/brainseq_phase2/blob/master/twas/README.md
1,022,527
1,022,546
4,316,013
CLOZUK+PGC2

View Slide

TWAS
DLPFC HIPPO
gene 7,683 (32.8%) 5,866 (25.1%)
exon 61,678 (16.2%) 47,583 (12.5%)
jxn 33,754 (12.5%) 27,088 (10.1%)
tx 14,118 (15.9%) 11,567 (13%)
Features with TWAS weights
Removed sex, snp PCs 1-5, expr PCs
Kept diagnosis
jaffelab::cleaningY()

View Slide

gene exon jxn tx
Other Risk Locus
−10 −5 0 5 −10 −5 0 5 −10 −5 0 5 −10 −5 0 5
−5
0
5
−5
0
5
DLPFC
HIPPO
in both
FALSE
TRUE
FDR <5%
None
DLPFC
HIPPO
Both
TWAS Z by brain region
TWAS

View Slide

View Slide

liigh2019

liigh2019

Leonardo Collado-Torres

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