Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
Intervene: a tool for intersection and visualization of multiple gene or genomic region sets
1. Intervene to
visualize
genomic region
sets
D. Denisko
Introduction
Description
Installation and
general usage
Modules
Venn diagram
Upset
Pairwise
heatmap
ShinyApp
Examples
Plots in
publications
Conclusion
Intervene: a tool for intersection and
visualization of multiple gene or genomic
region sets
Danielle Denisko
Tech Talk
June 13, 2018
Template from: www.overleaf.com
2. Intervene to
visualize
genomic region
sets
D. Denisko
Introduction
Description
Installation and
general usage
Modules
Venn diagram
Upset
Pairwise
heatmap
ShinyApp
Examples
Plots in
publications
Conclusion
Outline
Introduction
Description
Installation and general usage
Modules
Venn diagram
Upset
Pairwise heatmap
ShinyApp
Examples
Plots in publications
Conclusion
3. Intervene to
visualize
genomic region
sets
D. Denisko
Introduction
Description
Installation and
general usage
Modules
Venn diagram
Upset
Pairwise
heatmap
ShinyApp
Examples
Plots in
publications
Conclusion
Introduction
Summary:
intersect and visualize sets of genes
novel aspect: work specifically with genomic regions
Modules:
venn, upset, and pairwise
4. Intervene to
visualize
genomic region
sets
D. Denisko
Introduction
Description
Installation and
general usage
Modules
Venn diagram
Upset
Pairwise
heatmap
ShinyApp
Examples
Plots in
publications
Conclusion
Description
Use:
command line and Shiny web interface
Implementation:
Python 2.7 (also works with Python 3.4, 3.5, and 3.6)
R
Built upon:
pybedtools
Seaborn
Matplotlib
UpSetR
Corrplot
Venerable
heatmap.2
5. Intervene to
visualize
genomic region
sets
D. Denisko
Introduction
Description
Installation and
general usage
Modules
Venn diagram
Upset
Pairwise
heatmap
ShinyApp
Examples
Plots in
publications
Conclusion
Installation and general usage
To install:
pip install intervene
conda install intervene
Bitbucket and Github source code
Input:
genomic regions in BED, GFF, or VCF format
gene/name lists in plain text format
6. Intervene to
visualize
genomic region
sets
D. Denisko
Introduction
Description
Installation and
general usage
Modules
Venn diagram
Upset
Pairwise
heatmap
ShinyApp
Examples
Plots in
publications
Conclusion
Installation and general usage
Workflow:
Khan A and Mathelier A. 2017. BMC Bioinformatics. 18:287.
7. Intervene to
visualize
genomic region
sets
D. Denisko
Introduction
Description
Installation and
general usage
Modules
Venn diagram
Upset
Pairwise
heatmap
ShinyApp
Examples
Plots in
publications
Conclusion
Installation and general usage
There are three types of output plots:
Khan A and Mathelier A. 2017. BMC Bioinformatics. 18:287.
8. Intervene to
visualize
genomic region
sets
D. Denisko
Introduction
Description
Installation and
general usage
Modules
Venn diagram
Upset
Pairwise
heatmap
ShinyApp
Examples
Plots in
publications
Conclusion
Installation and general usage
Users can provide all possible bedtools intersect
options via --bedtools-options.
Figure 1: There are over 15 options for specifying overlaps in
bedtools intersect.
Image source: BEDTools suite web page.
9. Intervene to
visualize
genomic region
sets
D. Denisko
Introduction
Description
Installation and
general usage
Modules
Venn diagram
Upset
Pairwise
heatmap
ShinyApp
Examples
Plots in
publications
Conclusion
Modules
venn
classical Venn diagram
up to 6 sets
input: gene lists or genomic region sets
Shiny web interface provides some more flexibility:
weighted and unweighted Venn and Euler diagrams
different types of diagrams (up to 9 sets)
10. Intervene to
visualize
genomic region
sets
D. Denisko
Introduction
Description
Installation and
general usage
Modules
Venn diagram
Upset
Pairwise
heatmap
ShinyApp
Examples
Plots in
publications
Conclusion
Modules
venn
Figure 2: Venn (leftmost column) vs. Euler diagrams.
Venn: show all 2n possible regions
Euler: only show relevant (non-empty) regions
Image source: Wikipedia
11. Intervene to
visualize
genomic region
sets
D. Denisko
Introduction
Description
Installation and
general usage
Modules
Venn diagram
Upset
Pairwise
heatmap
ShinyApp
Examples
Plots in
publications
Conclusion
Modules
venn
intervene venn -i RC13-KO.narrowPeak RC13-WT.narrowPeak S12-KO.narrowPeak S12-WT.narrowPeak
--names=KO-rep1,WT-rep1,KO-rep2,WT-rep2 -o ~/intervene_plots/ --save-overlaps
--title="RNF169 ChIP-seq peaks" --project=RNF169_KO_WT --figtype=png
--figsize 12 12 --fontsize=24 --dpi=450
Figure 3: Intervene venn diagram.
12. Intervene to
visualize
genomic region
sets
D. Denisko
Introduction
Description
Installation and
general usage
Modules
Venn diagram
Upset
Pairwise
heatmap
ShinyApp
Examples
Plots in
publications
Conclusion
Modules
venn
Figure 4: Chow-Ruskey
Figure 5: Edwards
Figure 6: Squares
Figure 7: Battle
13. Intervene to
visualize
genomic region
sets
D. Denisko
Introduction
Description
Installation and
general usage
Modules
Venn diagram
Upset
Pairwise
heatmap
ShinyApp
Examples
Plots in
publications
Conclusion
Modules
venn
Figure 8: Intervene venn diagram with 6 sets.
14. Intervene to
visualize
genomic region
sets
D. Denisko
Introduction
Description
Installation and
general usage
Modules
Venn diagram
Upset
Pairwise
heatmap
ShinyApp
Examples
Plots in
publications
Conclusion
Modules
upset
easier to interpret when there are more than 4 sets
can be used effectively for 20-30 sets
15. Intervene to
visualize
genomic region
sets
D. Denisko
Introduction
Description
Installation and
general usage
Modules
Venn diagram
Upset
Pairwise
heatmap
ShinyApp
Examples
Plots in
publications
Conclusion
Modules
upset
Motivation:
Figure 9: Edwards-Venn diagram for banana gene clusters
comparison. D’Hont A et al. 2012. Nature. 488:7410.
16. Intervene to
visualize
genomic region
sets
D. Denisko
Introduction
Description
Installation and
general usage
Modules
Venn diagram
Upset
Pairwise
heatmap
ShinyApp
Examples
Plots in
publications
Conclusion
Modules
upset
intervene upset -i RC13-KO.narrowPeak RC13-WT.narrowPeak S12-KO.narrowPeak
S12-WT.narrowPeak --names=KO-rep1,WT-rep1,KO-rep2,WT-rep2 -o ~/intervene_plots/
--figtype=png --figsize 12 12 --showshiny
Figure 10: Intervene upset diagram.
17. Intervene to
visualize
genomic region
sets
D. Denisko
Introduction
Description
Installation and
general usage
Modules
Venn diagram
Upset
Pairwise
heatmap
ShinyApp
Examples
Plots in
publications
Conclusion
Modules
upset
1 #! / usr / bin /env R s c r i p t
2 l i b r a r y ( ”UpSetR” )
3 png ( ” I n t e r v e n e upset . png” , width =7200 , h e i g h t =3600 ,
4 r e s =300)
5 e x p r e s s i o n I n p u t <− c ( ’WT−rep2 ’ =2606 ,
6 ’KO−rep2 ’ =109 ,
7 ’KO−rep2&WT−rep2 ’ =44,
8 ’WT−rep1 ’ =39967 ,
9 ’WT−rep1&WT−rep2 ’ =12136 ,
10 ’WT−rep1&KO−rep2 ’ =39,
11 ’WT−rep1&KO−rep2&WT−rep2 ’ =114 ,
12 ’KO−rep1 ’ =77,
13 ’KO−rep1&WT−rep2 ’ =5,
14 ’KO−rep1&KO−rep2 ’ =21,
15 ’KO−rep1&KO−rep2&WT−rep2 ’ =22,
16 ’KO−rep1&WT−rep1 ’ =112 ,
17 ’KO−rep1&WT−rep1&WT−rep2 ’ =72,
18 ’KO−rep1&WT−rep1&KO−rep2 ’ =92,
19 ’KO−rep1&WT−rep1&KO−rep2&WT−rep2 ’ =290)
20 upset ( fromExpression ( e x p r e s s i o n I n p u t ) , n s e t s =4,
21 n i n t e r s e c t s =30, show . numbers=” yes ” ,
22 main . bar . c o l o r=”#ea5d4e ” ,
23 s e t s . bar . c o l o r=”#317eab ” ,
24 empty . i n t e r s e c t i o n s=NULL,
25 order . by = ” f r e q ” , number . a n g l e s = 0 ,
26 mainbar . y . l a b e l =”No . o f I n t e r s e c t i o n s ” ,
27 s e t s . x . l a b e l =” Set s i z e ” ,
28 t e x t . s c a l e=c ( 2 , 2 , 2 , 2 , 2 , 3 ) ) # added to a d j u s t f o n t s i z e s
29 i n v i s i b l e ( dev . o f f ( ) )
18. Intervene to
visualize
genomic region
sets
D. Denisko
Introduction
Description
Installation and
general usage
Modules
Venn diagram
Upset
Pairwise
heatmap
ShinyApp
Examples
Plots in
publications
Conclusion
Modules
upset
Figure 11: UpSet diagram from web application.
19. Intervene to
visualize
genomic region
sets
D. Denisko
Introduction
Description
Installation and
general usage
Modules
Venn diagram
Upset
Pairwise
heatmap
ShinyApp
Examples
Plots in
publications
Conclusion
Modules
pairwise
clustered heat map of pairwise associations
very large sets
metrics: number of overlaps, fraction of overlap,
Jaccard statistics, Fisher’s exact test, and
distribution of relative distances
heat map styles: tribar, dendrogram, pie, circle,
square, ellipse, etc.
clustering methods: various agglomerative options
20. Intervene to
visualize
genomic region
sets
D. Denisko
Introduction
Description
Installation and
general usage
Modules
Venn diagram
Upset
Pairwise
heatmap
ShinyApp
Examples
Plots in
publications
Conclusion
Modules
pairwise
Figure 12: Intervene pairwise plot.
21. Intervene to
visualize
genomic region
sets
D. Denisko
Introduction
Description
Installation and
general usage
Modules
Venn diagram
Upset
Pairwise
heatmap
ShinyApp
Examples
Plots in
publications
Conclusion
ShinyApp
Input:
does not accept genomic regions
venn: lists of names/genes/SNPs
upset: lists of names/genes/SNPs, binary data,
Intervene command line output listing all possible
combinations of sets
pairwise: lists of names/genes/SNPs, pairwise
matrix of number/fraction of overlap (can be
generated through Intervene on command line)
22. Intervene to
visualize
genomic region
sets
D. Denisko
Introduction
Description
Installation and
general usage
Modules
Venn diagram
Upset
Pairwise
heatmap
ShinyApp
Examples
Plots in
publications
Conclusion
ShinyApp
Figure 13: Screenshot from Intervene’s upset module
ShinyApp.
23. Intervene to
visualize
genomic region
sets
D. Denisko
Introduction
Description
Installation and
general usage
Modules
Venn diagram
Upset
Pairwise
heatmap
ShinyApp
Examples
Plots in
publications
Conclusion
Plots in publications
Figure 14: Coregulated and antiregulated genes (with lncRNA)
in various yeast colonies.
Wilkinson D et al. 2018. Oxid Med Cell Longev.
24. Intervene to
visualize
genomic region
sets
D. Denisko
Introduction
Description
Installation and
general usage
Modules
Venn diagram
Upset
Pairwise
heatmap
ShinyApp
Examples
Plots in
publications
Conclusion
Plots in publications
Figure 15: Differentially expressed genes over time after influenza
treatment. Black: up- or down-regulated genes, red: upregulated genes,
blue: downregulated genes. Top: PBMCs, bottom: B cells.
Jensen TL et al. 2018. F1000Research. 6:2162.
25. Intervene to
visualize
genomic region
sets
D. Denisko
Introduction
Description
Installation and
general usage
Modules
Venn diagram
Upset
Pairwise
heatmap
ShinyApp
Examples
Plots in
publications
Conclusion
Conclusion
Pros:
simple command line tool for generating quick plots
convenient for visualizing genomic region sets
some customization (via output scripts and/or
ShinyApp)
Cons:
limited ability to customize, even in ShinyApp
limited plot types in comparison to ShinyApp