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  • 1. Introduction Spatio Clustering of Suicide Data in Japan Application of RnavGraph Summary and Future Studies . . . . . . . . . . . . . . . . . . . . Visualization of high dimensional and large data set by RnavGraph and its application of suicide data in Japan Takafumi Kubota1 , Makoto Tomita2 , Fumio Ishioka3 and Toshiharu Fujita1 1 The Institute of Statistical Mathematics 2 Tokyo Medical and Dental University 3 Okayama University December 26, 2011 . . . . . .Kubota, T., Tomita, M., Ishioka, F. and Fujita, T.Visualization of high dimensional and large data set by RnavGraph and its application of suicide data in Japan
  • 2. Introduction Spatio Clustering of Suicide Data in Japan Application of RnavGraph Summary and Future Studies . . . . . . . . . . . . . . . . . . . . 1 Introduction Statistics of Suicide in Japan Objective 2 Spatio Clustering of Suicide Data in Japan Statistics of Community for the Death from Suicide Heirachical cluster analysis 3 Application of RnavGraph Install Application of the Suicide data 4 Summary and Future Studies . . . . . .Kubota, T., Tomita, M., Ishioka, F. and Fujita, T.Visualization of high dimensional and large data set by RnavGraph and its application of suicide data in Japan
  • 3. Introduction Spatio Clustering of Suicide Data in Japan Application of RnavGraph Summary and Future Studies . . . . . . . . . . . . . . . . . . . .Statistics of Suicide in Japan We briefly introduce statistics of suicide in Japan at the points of When? Where? Who? Sex Age-group We changed the color of Age-group to red because it is our objective of this presentation. . . . . . .Kubota, T., Tomita, M., Ishioka, F. and Fujita, T.Visualization of high dimensional and large data set by RnavGraph and its application of suicide data in Japan
  • 4. Introduction Spatio Clustering of Suicide Data in Japan Application of RnavGraph Summary and Future Studies . . . . . . . . . . . . . . . . . . . .Statistics of Suicide in JapanWhen? (Time Series of the Number of Suicide) White paper of suicide prevention (2011) . . . . . .Kubota, T., Tomita, M., Ishioka, F. and Fujita, T.Visualization of high dimensional and large data set by RnavGraph and its application of suicide data in Japan
  • 5. Introduction Spatio Clustering of Suicide Data in Japan Application of RnavGraph Summary and Future Studies . . . . . . . . . . . . . . . . . . . .Statistics of Suicide in Japan The number of suicide rapidly increased from 1997 to 1998 Burst of the economic bubble (1990-1992) Economic recession (1993-1997) → Bankruptcy, corporate downsizing, unemployment,... In this study, we use the time period of 1988-1992; before rapidly increased time periods For our future studies, we will use other time periods: → (1988-1992),1993-1997,1998-2002,2003-2007,... Individually (Purely spatial clustering) Simultaneously (Spatio-temporal clustering) . . . . . .Kubota, T., Tomita, M., Ishioka, F. and Fujita, T.Visualization of high dimensional and large data set by RnavGraph and its application of suicide data in Japan
  • 6. Introduction Spatio Clustering of Suicide Data in Japan Application of RnavGraph Summary and Future Studies . . . . . . . . . . . . . . . . . . . .Statistics of Suicide in JapanWhere? (Hotspot and Coolspot) The results of spatial clustering. The color legend is as follows Hotspot Most likely cluster Second most likely cluster Coolspot Most likely cluster Second most likely cluster Otherwise Kubota, et al. (2011) . . . . . .Kubota, T., Tomita, M., Ishioka, F. and Fujita, T.Visualization of high dimensional and large data set by RnavGraph and its application of suicide data in Japan
  • 7. Introduction Spatio Clustering of Suicide Data in Japan Application of RnavGraph Summary and Future Studies . . . . . . . . . . . . . . . . . . . .Statistics of Suicide in JapanHotspots and Coolspots of Male Case in 1988-1992 . . . . . .Kubota, T., Tomita, M., Ishioka, F. and Fujita, T.Visualization of high dimensional and large data set by RnavGraph and its application of suicide data in Japan
  • 8. Introduction Spatio Clustering of Suicide Data in Japan Application of RnavGraph Summary and Future Studies . . . . . . . . . . . . . . . . . . . .Statistics of Suicide in JapanWho? (Sex and Age Group of the Number of Suicide) White paper of suicide prevention (2011) . . . . . .Kubota, T., Tomita, M., Ishioka, F. and Fujita, T.Visualization of high dimensional and large data set by RnavGraph and its application of suicide data in Japan
  • 9. Introduction Spatio Clustering of Suicide Data in Japan Application of RnavGraph Summary and Future Studies . . . . . . . . . . . . . . . . . . . .ObjectiveObjective From the bar chart, we can find differences of proportions between age groups. → Our goal is to find characteristics of age-grouped spatial data of suicide in Japan. . . . . . .Kubota, T., Tomita, M., Ishioka, F. and Fujita, T.Visualization of high dimensional and large data set by RnavGraph and its application of suicide data in Japan
  • 10. Introduction Spatio Clustering of Suicide Data in Japan Application of RnavGraph Summary and Future Studies . . . . . . . . . . . . . . . . . . . .ObjectiveAnalysis Procedure 1 Dendrogram; the results of hierarchical clustering 2 Dynamic tree cut 3 Reasoning for each cluster . . . . . .Kubota, T., Tomita, M., Ishioka, F. and Fujita, T.Visualization of high dimensional and large data set by RnavGraph and its application of suicide data in Japan
  • 11. Introduction Spatio Clustering of Suicide Data in Japan Application of RnavGraph Summary and Future Studies . . . . . . . . . . . . . . . . . . . .ObjectiveHow we apply RnavGraph to the results of clustering? To visualize the result of clustering, we will find the common points in same cluster. . . . . . .Kubota, T., Tomita, M., Ishioka, F. and Fujita, T.Visualization of high dimensional and large data set by RnavGraph and its application of suicide data in Japan
  • 12. Introduction Spatio Clustering of Suicide Data in Japan Application of RnavGraph Summary and Future Studies . . . . . . . . . . . . . . . . . . . .Statistics of Community for the Death from Suicide Statistics of Community for the Death from Suicide (Fujita, 2009) was updated from the Ministry of Health, Labour and Welfare demographic survey of death Population Survey Death Report of the Ministry of Health, Labour and Welfare Time: (73-77, 78-82, 83-87,) 88-92, (93-97, 98-02, 02-07 , 08-09) Place: 354 Secondary medical care zones Sex: Male (, Female) 16 age groups → 4 age groups (weighted average) 10-29(10-14,15-19,20-24,25-29) 30-49(30-34,35-39,40-44,45-49) 50-69(50-54,55-59,60-64,65-69) 70+(70-74,75-79,80-84,85+) (Ways, Marriage and Job ) . . . . . .Kubota, T., Tomita, M., Ishioka, F. and Fujita, T.Visualization of high dimensional and large data set by RnavGraph and its application of suicide data in Japan
  • 13. Introduction Spatio Clustering of Suicide Data in Japan Application of RnavGraph Summary and Future Studies . . . . . . . . . . . . . . . . . . . .Heirachical cluster analysisResult; 1900 male From the result, it seems that there are four groups. . . . . . .Kubota, T., Tomita, M., Ishioka, F. and Fujita, T.Visualization of high dimensional and large data set by RnavGraph and its application of suicide data in Japan
  • 14. Introduction Spatio Clustering of Suicide Data in Japan Application of RnavGraph Summary and Future Studies . . . . . . . . . . . . . . . . . . . .Heirachical cluster analysisChoropleth map 4 clusters cut by dynamicTreeCut Langfelder, et al. . . . . . .Kubota, T., Tomita, M., Ishioka, F. and Fujita, T.Visualization of high dimensional and large data set by RnavGraph and its application of suicide data in Japan
  • 15. Introduction Spatio Clustering of Suicide Data in Japan Application of RnavGraph Summary and Future Studies . . . . . . . . . . . . . . . . . . . .InstallWhat is RnavGraph? RnavGraph provides interactive visualization tools for exploring high dimensional space through lower dimensional trajectories, based on the concepts first presented in Hurley and Oldford (2011). . . . . . .Kubota, T., Tomita, M., Ishioka, F. and Fujita, T.Visualization of high dimensional and large data set by RnavGraph and its application of suicide data in Japan
  • 16. Introduction Spatio Clustering of Suicide Data in Japan Application of RnavGraph Summary and Future Studies . . . . . . . . . . . . . . . . . . . .InstallInstall Environment Windows 7 (64 bit) R 2.14.0 (execute as Administrator(?)) 1 install.packages(c("PairViz", "scagnostics", 2 "rgl", "grid", "MASS", "RGtk2", "hexbin", "vegan"), 3 dependencies = TRUE) 4 source("http://www.bioconductor.org/biocLite.R") 5 biocLite("graph") 6 biocLite("RBGL") 7 biocLite("RDRToolbox") 8 install.packages("RnavGraph") 9 install.packages("RnavGraphImageData") . . . . . .Kubota, T., Tomita, M., Ishioka, F. and Fujita, T.Visualization of high dimensional and large data set by RnavGraph and its application of suicide data in Japan
  • 17. Introduction Spatio Clustering of Suicide Data in Japan Application of RnavGraph Summary and Future Studies . . . . . . . . . . . . . . . . . . . .InstallHello RnavGraph World! 1 library(RnavGraph) 2 ng.iris <- ng_data(name = "iris", data = iris[,1:4], 3 shortnames = c(’s.L’, ’s.W’, ’p.L’, ’p.W’), 4 group = iris$Species, 5 labels = substr(iris$Species,1,2)) 6 navGraph(ng.iris) . . . . . .Kubota, T., Tomita, M., Ishioka, F. and Fujita, T.Visualization of high dimensional and large data set by RnavGraph and its application of suicide data in Japan
  • 18. Introduction Spatio Clustering of Suicide Data in Japan Application of RnavGraph Summary and Future Studies . . . . . . . . . . . . . . . . . . . .Application of the Suicide dataData suigm90 int.csv secid age1 age2 age3 age4 group 1 101 11.91 28.50 32.98 50.45 1 2 102 9.70 40.21 46.79 36.73 2 3 103 18.93 27.49 34.52 49.23 1 ... ... ... ... ... ... ... . . . . . .Kubota, T., Tomita, M., Ishioka, F. and Fujita, T.Visualization of high dimensional and large data set by RnavGraph and its application of suicide data in Japan
  • 19. Introduction Spatio Clustering of Suicide Data in Japan Application of RnavGraph Summary and Future Studies . . . . . . . . . . . . . . . . . . . .Application of the Suicide dataApplication of Suicide Data 1 require(RnavGraph) 2 sui.m90c <- read.csv("suigm90_int.csv") 3 ng.suim90c <- ng_data(name = "SuicideMale90", 4 data = sui.m90c[,2:5]) 5 ng_set(ng.suim90c, "group") <- sui.m90c[,6] 6 navGraph(ng.suim90c) . . . . . .Kubota, T., Tomita, M., Ishioka, F. and Fujita, T.Visualization of high dimensional and large data set by RnavGraph and its application of suicide data in Japan
  • 20. Introduction Spatio Clustering of Suicide Data in Japan Application of RnavGraph Summary and Future Studies . . . . . . . . . . . . . . . . . . . .Application of the Suicide dataOutput of navGraph . . . . . .Kubota, T., Tomita, M., Ishioka, F. and Fujita, T.Visualization of high dimensional and large data set by RnavGraph and its application of suicide data in Japan
  • 21. Introduction Spatio Clustering of Suicide Data in Japan Application of RnavGraph Summary and Future Studies . . . . . . . . . . . . . . . . . . . .Application of the Suicide dataApplication of Suicide Data (scagNav) 1 ng.sui<-ng_data(name="suicide", 2 data=sui.m90c[,2:5], 3 shortnames=c("a1","a2","a3","a4"), 4 group=sui.m90c[,6]) 5 nav.sui <- scagNav(data = ng.sui, 6 scags = c("Monotonic", "NotMonotonic", "Clumpy", 7 "NotClumpy", "Convex", "NotConvex", 8 "Stringy", "NotStringy", "Skinny", 9 "NotSkinny", "Outlying","NotOutlying", 10 "Sparse", "NotSparse", "Striated", 11 "NotStriated", "Skewed", "NotSkewed"), 12 topFrac = 0.2, combineFn = max, 13 glyphs = shortnames(ng.sui), sep = ’:’) . . . . . .Kubota, T., Tomita, M., Ishioka, F. and Fujita, T.Visualization of high dimensional and large data set by RnavGraph and its application of suicide data in Japan
  • 22. Introduction Spatio Clustering of Suicide Data in Japan Application of RnavGraph Summary and Future Studies . . . . . . . . . . . . . . . . . . . .Application of the Suicide dataOutputs of scagNav . . . . . .Kubota, T., Tomita, M., Ishioka, F. and Fujita, T.Visualization of high dimensional and large data set by RnavGraph and its application of suicide data in Japan
  • 23. Introduction Spatio Clustering of Suicide Data in Japan Application of RnavGraph Summary and Future Studies . . . . . . . . . . . . . . . . . . . . Reasoning group 3 (purple): High rate →Large square group 4 (orange): Low rate →Small square group 2 (green): High rate of age 1 (10-29) →Long right hand group 1 (blue): Others For our future studies, we will use other time periods: → (1988-1992),1993-1997,1998-2002,2003-2007,... Individually (Purely spatial clustering) Simultaneously (Spatio-temporal clustering) . . . . . .Kubota, T., Tomita, M., Ishioka, F. and Fujita, T.Visualization of high dimensional and large data set by RnavGraph and its application of suicide data in Japan
  • 24. Introduction Spatio Clustering of Suicide Data in Japan Application of RnavGraph Summary and Future Studies . . . . . . . . . . . . . . . . . . . .REFERENCES (1) Fujita, T. (2009). Statistics of Community for the Death from Suicide. National Institute of Mental Health, National Center of Neurology and Psychiatry, Japan. Hurley, C. and Oldford, R.W. (2011). Graphs as navigational infrastructure for high dimensional data spaces, (Computational Statistics, to appear). Kubota, T., Tomita, M., Ishioka, F. and Fujita, T. (2011). Spatial Autocorrelation Statistics and Spatial Clustering in the Areas in Japan with Low Suicide Rates, Joint2011, pp. ??? Waddell, A. and Oldford, W. (2011). RnavGraph: an R package to visualize high dimensional data using graphs as navigational infrastructure. http://cran.r-project.org/web/packages/RnavGraph/vignettes/ RnavGraph.pdf(Dec. 26, 2011) White paper of suicide prevention (2011). Cabinet Office (in Japanese) http://www8.cao.go.jp/jisatsutaisaku/whitepaper/index-w.html (Dec. 17, 2011) . . . . . .Kubota, T., Tomita, M., Ishioka, F. and Fujita, T.Visualization of high dimensional and large data set by RnavGraph and its application of suicide data in Japan
  • 25. Introduction Spatio Clustering of Suicide Data in Japan Application of RnavGraph Summary and Future Studies . . . . . . . . . . . . . . . . . . . .REFERENCES (2) Langfelder, P., Zhang, B. and Horvath, S. Defining clusters from a hierarchical cluster tree:the Dynamic Tree Cut library for R http://www.genetics.ucla.edu/labs/horvath/ CoexpressionNetwork/BranchCutting/ (Dec. 26, 2011) . . . . . .Kubota, T., Tomita, M., Ishioka, F. and Fujita, T.Visualization of high dimensional and large data set by RnavGraph and its application of suicide data in Japan
  • 26. Introduction Spatio Clustering of Suicide Data in Japan Application of RnavGraph Summary and Future Studies . . . . . . . . . . . . . . . . . . . .Q&A Thank you very much for your kind attention. Takafumi Kubota (The Institute of Statistical Mathematics) tkubota@ism.ac.jp . . . . . .Kubota, T., Tomita, M., Ishioka, F. and Fujita, T.Visualization of high dimensional and large data set by RnavGraph and its application of suicide data in Japan