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JohnGriffiths/ network_visualizations_in_R

Last active August 29, 2015 13:56
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Network Visualizations in R - Some examples in the attached for R. This is for simulated FC data of 110 rois but could be anything that has centroids. Nothing too fancy but there are many ways to extend this. You can also easily make movies and stuff if so inclined. And using shiny http://www.rstudio.com/shiny/ you could have something like this…
Raw
3dgplotexamples.R
#install packages
install.packages("igraph")
install.packages("qgraph")
install.packages("NetworkAnalysis")
install.packages("ggplot2")
install.packages("gplots")
install.packages("gdata")
install.packages("lavaan")
install.packages("sna")
install.packages("rgl")
#loading packages
library(igraph)
library(NetworkAnalysis)
library(ggplot2)
library(gplots)
library(lavaan)
library(gdata)
library(sna)
library(qgraph)
library(rgl)
#the belew examples model the connectivity between 110 ROIS in various ways
#load and define data
data=read.csv("dataexample.csv",header=T) #connectivity
coor=data[,1:3] #x y z coordinates for ROIS
lobes=data[,4] #defining rois as being part of 5 lobes
names=as.character(data[,5]) #roilabels
fc=read.csv("fcexample.csv",header=F)
rownames(fc)=names
#calculating betweenness (used later)
qgraphtemp=qgraph(fc)
networkstats=centrality(qgraphtemp)
bet=networkstats$Betweenness
bet=((bet-min(bet))/(max(bet)-min(bet))+0.01) #scaling betweenness
#Plotting examples Nodesize= betweenness, positive connections= green, negative = red.
#labels only shown for nodes with high betweenness centrality
# 1) basic plot unthresholded: not very useful, no structure and too many connections
gplot3d(fc,thres=.7)
# 2) Bit better: Using ROI coordinates to create 3d structure. Still not great
gplot3d(fc,coord=coor,thres=1.4,displaylabels=F)
# 3) Better still: Stringent thresholding, increasing node sizes nodes iets groter and
#colour code lobes; black/Frontal,green/temporal, red/parietal, blue/occipital, turqouise=subcortical
gplot3d(fc,coord=coor,vertex.radius=1.5,thres=1.6,vertex.col=lobes)
# 4) Adding information: Nodesizes varies as a function of betweenness
gplot3d(fc,coord=coor,vertex.radius=bet*4,thres=1.6,vertex.col=lobes,displaylabels=F)
# 5) Final: Conditional labeling: Show ROI names, but only for nodes (rois) that are top 10% betweenness. You can zoom, scale
#some code to generate conditional labels
betthres=cbind(names,bet)
for (f in 1:110)
{
thresbet=quantile(bet,0.90)
newnamesx=ifelse(betthres[f,2]>thresbet,betthres[f,1],"")
betthres[f,1]=newnamesx
}
labelsnew=betthres[,1]
#Plot
gplot3d(fc,coord=coor,label=labelsnew,vertex.radius=2,thres=1.6,vertex.col=lobes,displaylabels=T)
Raw
dataexample.csv
x y z lobes names
-24.95425577 52.99589293 7.536043053 1 LFrontalPole
-36.70517241 1.443103448 -0.172413793 1 LInsularCortex
-14.19385343 18.7927502 56.64223798 1 LSuperiorFrontalGyrus
-38.32087114 18.58511797 42.33901996 1 LMiddleFrontalGyrus
-49.99341021 28.57001647 8.803953871 1 LInferiorFrontalGyrus,parstriangularis
-50.92729767 14.75171468 15.31138546 1 LInferiorFrontalGyrus,parsopercularis
-34.26722533 -11.51350093 49.31238361 1 LPrecentralGyrus
-40.62723404 11.14382979 -29.70297872 3 LTemporalPole
-56.18972332 -3.652173913 -8.324110672 3 LSuperiorTemporalGyrus,anteriordivision
-60.64538198 -27.36374002 2.364880274 3 LSuperiorTemporalGyrus,posteriordivision
-57.61434978 -4.044843049 -22.35426009 3 LMiddleTemporalGyrus,anteriordivision
-61.31338583 -27.28503937 -11.54330709 3 LMiddleTemporalGyrus,posteriordivision
-57.84290739 -53.07151231 0.834701055 3 LMiddleTemporalGyrus,temporooccipitalpart
-48.29090909 -5.078787879 -39.35151515 3 LInferiorTemporalGyrus,anteriordivision
-53.65025126 -28.59497487 -26.01809045 3 LInferiorTemporalGyrus,posteriordivision
-51.93678161 -53.47701149 -16.59770115 3 LInferiorTemporalGyrus,temporooccipitalpart
-38.5275634 -27.75413451 51.86383682 1 LPostcentralGyrus
-29.38026225 -49.55279503 57.65217391 2 LSuperiorParietalLobule
-56.92811839 -32.794926 37.29598309 2 LSupramarginalGyrus,anteriordivision
-54.87452471 -46.20342205 33.4391635 2 LSupramarginalGyrus,posteriordivision
-50.39029536 -55.6814346 29.97468354 2 LAngularGyrus
-32.1691221 -72.87426842 38.01897074 4 LLateralOccipitalCortex,superoirdivision
-45.18003914 -75.61643836 -2.000978474 4 LLateralOccipitalCortex,inferiordivision
-10.30427892 -74.96354992 8.101426307 4 LIntracalcarineCortex
-5.132075472 43.54245283 -18.33962264 1 LFrontalMedialCortex
-5.605015674 -2.567398119 56.25705329 1 LJuxtapositionalLobuleCortex(formerlySupplementaryMotorCortex)
-5.249027237 20.6614786 -15.06225681 1 LSubcallosalCortex
-6.486526946 36.82784431 20.88023952 1 LParacingulateGyrus
-4.750750751 18.08208208 24.64464464 1 LCingulateGyrus,anteriordivision
-5.982213439 -37.56521739 29.85573123 3 LCingulateGyrus,posteriordivision
-7.895076675 -59.96045198 37.40193705 2 LPrecuneousCortex
-8.474103586 -80.29083665 27.23904382 4 LCunealCortex
-29.70170288 23.8109219 -16.4979448 1 LFrontalOrbitalCortex
-22.13405797 -9.101449275 -30.83333333 3 LParahippocampalGyrus,anteriordivision
-21.88020833 -32.44270833 -17.03125 3 LParahippocampalGyrus,posteriordivision
-12.51114024 -65.35124509 -5.44429882 4 LLingualGyrus
-31.75316456 -4.588607595 -42.20253165 3 LTemporalFusiformCortex,anteriordivision
-36.07560137 -29.50057274 -25.04009164 3 LTemporalFusiformCortex,posteriordivision
-33.55864198 -53.68518519 -16.05246914 3 LTemporalOccipitalFusiformCortex
-26.42764579 -76.66306695 -13.66738661 4 LOccipitalFusiformGyrus
-39.61325967 18.44751381 4.541436464 1 LFrontalOperculumCortex
-47.87804878 -8.331300813 11.75406504 1 LCentralOpercularCortex
-48.44444444 -31.64583333 20.38541667 2 LParietalOperculumCortex
-46.56666667 -5.916666667 -7.494444444 3 LPlanumPolare
-45.26875 -20.21875 7.075 3 LHeschl'sGyrus(includesH1andH2)
-52.51407129 -29.78611632 10.91932458 3 LPlanumTemporale
-9.75 -72.08333333 14.91666667 4 LSupracalcarineCortex
-16.98674744 -96.52858766 6.861037486 4 LOccipitalPole
25.85292706 52.29198656 8.148272553 1 RFrontalPole
37.56477561 2.574089754 -0.32514818 1 RInsularCortex
13.90637293 19.62470496 56.6404406 1 RSuperiorFrontalGyrus
39.36977743 18.76298321 43.03319016 1 RMiddleFrontalGyrus
52.31048387 28 7.762096774 1 RInferiorFrontalGyrus,parstriangularis
52.40610687 15.4778626 16.14961832 1 RInferiorFrontalGyrus,parsopercularis
33.81061492 -10.95300444 50.57096095 1 RPrecentralGyrus
40.70055061 13.06903854 -29.83396866 3 RTemporalPole
57.67164179 -0.507462687 -10.23880597 3 RSuperiorTemporalGyrus,anteriordivision
60.30849948 -23.29275971 1.576075551 3 RSuperiorTemporalGyrus,posteriordivision
57.90547264 -1.308457711 -24.70149254 3 RMiddleTemporalGyrus,anteriordivision
61.49482072 -22.39043825 -12.78087649 3 RMiddleTemporalGyrus,posteriordivision
58.40660295 -49.15899218 1.537793223 3 RMiddleTemporalGyrus,temporooccipitalpart
46.32807571 -2.391167192 -41.26182965 3 RInferiorTemporalGyrus,anteriordivision
53.59450898 -23.43822598 -28.26187962 3 RInferiorTemporalGyrus,posteriordivision
54.2377261 -49.84754522 -16.81395349 3 RInferiorTemporalGyrus,temporooccipitalpart
37.75512703 -26.23875115 52.64401592 1 RPostcentralGyrus
29.29266621 -47.77107608 59.07607951 2 RSuperiorParietalLobule
58.54522613 -27.11055276 37.91708543 2 RSupramarginalGyrus,anteriordivision
55.28914664 -40.46561723 33.82435791 2 RSupramarginalGyrus,posteriordivision
52.05475702 -51.8275154 32.36550308 2 RAngularGyrus
33.03731343 -71.1119403 38.98341625 4 RLateralOccipitalCortex,superoirdivision
45.61271394 -73.99804401 -1.684107579 4 RLateralOccipitalCortex,inferiordivision
11.37402597 -73.78181818 8.332467532 4 RIntracalcarineCortex
4.184782609 43.32608696 -18.96014493 1 RFrontalMedialCortex
5.1678487 -2.574468085 57.87706856 1 RJuxtapositionalLobuleCortex(formerlySupplementaryMotorCortex)
4.171974522 20.75796178 -14.96178344 1 RSubcallosalCortex
5.741293532 36.59825871 23.03233831 1 RParacingulateGyrus
4.305084746 18.56371626 24.19460138 1 RCingulateGyrus,anteriordivision
5.47925608 -35.77825465 30.41344778 3 RCingulateGyrus,posteriordivision
7.938314785 -58.72877583 38.78537361 2 RPrecuneousCortex
8.08 -78.95448276 27.96137931 4 RCunealCortex
29.22906574 23.08235294 -16.25190311 1 RFrontalOrbitalCortex
22.37620579 -8.067524116 -30.69131833 3 RParahippocampalGyrus,anteriordivision
23.01875 -30.4 -17.01875 3 RParahippocampalGyrus,posteriordivision
12.92398922 -64.04743935 -4.944474394 4 RLingualGyrus
31.14285714 -2.959183673 -42.44217687 3 RTemporalFusiformCortex,anteriordivision
36.32454924 -24.36338419 -27.71705964 3 RTemporalFusiformCortex,posteriordivision
35.05237515 -49.97076736 -16.72350792 3 RTemporalOccipitalFusiformCortex
27.34772727 -75.24545455 -12.30227273 4 ROccipitalFusiformGyrus
41.21846154 18.59692308 4.72 1 RFrontalOperculumCortex
49.32815965 -5.594235033 11.08203991 1 RCentralOpercularCortex
48.83241252 -27.43646409 21.41804788 2 RParietalOperculumCortex
48.10282776 -3.542416452 -7.141388175 3 RPlanumPolare
46.01408451 -17.45070423 7.014084507 3 RHeschl'sGyrus(includesH1andH2)
54.93078759 -25.16945107 12.10023866 3 RPlanumTemporale
6.645502646 -75.13227513 13.91534392 4 RSupracalcarineCortex
17.05654649 -95.19544592 8.399240987 4 ROccipitalPole
-10.0301941 -19.08123652 6.369518332 5 LeftThalamus
-12.98591549 9.228873239 9.690140845 5 LeftCaudate
-25.08794788 0.319218241 0.319218241 5 LeftPutamen
-18.96153846 -5.006410256 -1.256410256 5 LeftPallidum
-25.32401525 -23.14612452 -13.94155019 5 LeftHippocampus
-23.11309524 -4.81547619 -17.75595238 5 LeftAmygdala
-9.444444444 11.68518519 -7.296296296 5 LeftAccumbens
10.88130334 -18.36772692 6.538401862 5 RightThalamus
13.30873786 10.20194175 10.51650485 5 RightCaudate
25.5 1.9125 0.255 5 RightPutamen
19.88721805 -3.812030075 -1.218045113 5 RightPallidum
26.4963925 -20.995671 -14.28860029 5 RightHippocampus
23.14956012 -4.017595308 -17.71847507 5 RightAmygdala
9.465116279 12.06976744 -6.627906977 5 RightAccumbens
Raw
fcexample.csv
0 1.174868237 1.218299835 1.517848087 1.378005983 1.254433307 0.180333867 0.641421234 0.307734005 0.635542771 0.391948246 0.56555864 0.402809409 0.550527708 -0.128499187 0.072129382 0.275146956 0.594283693 0.528044199 0.869895819 1.532606938 0.969153267 0.235908828 0.206654661 0.317688442 0.037775402 0.521990269 1.15828353 0.932683138 1.085114578 1.100568399 0.739593601 0.656939496 0.210592128 0.605180443 0.189855582 0.543278802 0.435487611 0.016327732 0.044386898 1.177397505 0.352999763 0.15950828 0.945980882 0.689453735 1.25643684 0.369140773 0.342410751 0.996162595 0.507923055 1.096365517 0.613489603 0.487121116 0.205986805 0.28812122 0.542592809 0.513940275 0.144536881 -0.064812811 0.548398442 0.110616257 0.192322676 0.174210204 0.51097322 -0.083072409 0.296695396 0.099926286 0.527135587 1.17092521 0.55899071 -0.114266642 0.26752518 0.679261048 0.236372295 -0.221380664 1.079615521 0.997177869 1.145312615 1.076273124 0.748147847 0.474117862 0.641833731 -0.371613443 0.444841833 -0.020874342 0.362060403 -0.1680657 0.393032689 0.462819564 0.71150868 0.024734061 0.971186955 0.818957221 0.693231766 0.456396624 0.576923746 1.200687684 1.041618461 0.705263629 0.341307491 0.713541102 -0.147765869 0.452682431 1.091407283 1.188162686 0.202932254 0.463686523 0.296825579 0.502955569 0.793926417
-0.103140848 0 0.163642287 -0.198166196 0.094943669 -0.017339633 0.164725284 0.211366942 0.350681341 0.41781588 -0.306110592 0.24992751 0.047328138 -0.019335865 -0.15974678 0.247483277 -0.357223601 0.160877014 0.340018993 0.188650925 0.031248171 -0.068593239 0.088722168 0.261080207 0.336664461 0.297138516 0.100257147 0.233923661 0.145103796 0.429735792 0.391863352 -0.137132492 0.448619405 -0.120030988 0.220846382 -0.019633833 0.100916436 -0.11917302 0.149924124 0.279294853 0.613267531 0.709235617 0.312936754 0.832237981 0.532971829 0.099154698 0.00936695 0.791441469 0.458107838 1.057498408 0.329725159 -0.091245774 0.43249401 0.613595194 0.305984025 0.166573794 0.395715392 0.189565692 0.292056088 -0.136896112 0.493340056 -0.405556594 -0.092129701 0.035090856 0.022937411 -0.096024938 0.513631013 0.161214013 -0.043607688 0.14873369 0.324018955 0.301313779 0.125127817 0.201143077 0.098570587 0.546822268 0.334934127 0.179823567 0.493576132 0.125300875 0.591933363 0.272152476 -0.42293492 0.370992432 0.067671149 -0.180315408 -0.047859041 0.334587446 0.817362215 0.862425907 0.188882015 0.934212666 0.886518215 0.20229022 0.433693167 0.477853567 0.33291144 0.165574606 -0.073053024 -0.03728248 -0.03197431 0.177339554 -0.027537419 0.292029176 -0.011950182 0.058320771 -0.018806399 -0.112174226 -0.082585825 0.170379671
0.442910729 0.537095974 0 0.876848501 0.920805734 1.16863053 0.436261067 0.009226898 0.220029689 0.153552624 0.178519346 0.418162098 0.689394768 0.573302688 -0.022876599 -0.013083704 0.599300642 0.578288276 0.338119923 0.200419263 0.757807111 0.457900663 0.341195205 0.344414396 0.551987713 0.771133093 0.62291216 0.452264445 0.682335194 0.775740261 0.92293831 0.698105766 0.294860967 0.500345857 0.593896711 0.364924495 0.603126296 0.056069605 0.637537209 0.418016149 -0.002502374 0.006938889 0.836725892 -0.142793158 0.247350976 0.882668087 0.569319657 0.920597385 0.341828244 0.076518859 0.895812654 0.537151015 0.161232507 0.346798599 0.486369905 0.550198672 0.053461979 0.116763218 0.601026925 0.570312786 0.294271063 0.232772893 0.217030627 0.246630432 0.384820596 0.297644552 0.472813954 -0.251770856 0.240011304 0.818333078 0.584215856 0.121110767 0.371851265 0.735755953 0.135917888 0.594012963 0.789508217 0.866478029 1.04128393 0.648032177 0.489581789 0.599506768 0.653205396 0.609057001 -0.151856636 0.131673744 0.244364701 0.38458242 -0.18465516 0.307489592 0.296473366 0.140410652 0.367074485 0.123059047 0.580845841 0.70748613 0.986866917 0.907625778 0.153488122 0.249748459 0.198466005 0.217410484 0.116774758 0.802657494 0.518798708 0.272727591 0.015908833 0.733820837 0.015369087 -0.003545753
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Raw
NetworkVisualizationsInR
(This is thanks to Rogier Kievit)
Some examples in the attached for R. This is for simulated FC data of 110 rois but could be anything that has centroids. Nothing too fancy but there are many ways to extend this. You can also easily make movies and stuff if so inclined. And using shiny http://www.rstudio.com/shiny/ you could have something like this hosted on your website where people can tweak the parameters (thresholding, nodesize) just using interactive sliders.
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