data mining データ・マイニング

Data Miningデータ・マイニング

2014/07/14Unit Statistical Genetics

Ryo Yamada統計遺伝学分野

山田　亮

A blank sheet for you to answer Qs during the class,

that is collected at the end of class.Put your name and lab on the top.

何も書いていない紙は講義中の質問への回答を書くためのものです。

講義終了時、回収。名前と所属を用紙の一番上に書き

なさい。

Glomerulus 腎糸球体Q “Sketch スケッチせよ”

Model モデル Q2 “Sketch スケッチせよ”

QDifference between the photo and

the diagram?写真と模式図の違いは？

• Write your opinion. 意見を書け

The diagramkeeps/stresses

something and

throw awaysomething

in the photo.

模式図は写真にある何かを取り出し、何かを捨

てている

QDifference between PRE-filter and

POST-filter?フィルタリング前後での違いは？• Write your opinion. 意見を書け

QThere are three 2-D images.

What are lost?２次元投影図が３枚ある。

何が失われている？

• Write your opinion. 意見を書け

Figure 2. Correlation between age of females and parturition date.

Barclay RMR (2012) Variable Variation: Annual and Seasonal Changes in Offspring Sex Ratio in a Bat. PLoS ONE 7(5): e36344. doi:10.1371/journal.pone.0036344http://www.plosone.org/article/info:doi/10.1371/journal.pone.0036344

Figure 2. Correlation between age of females and parturition date.

Barclay RMR (2012) Variable Variation: Annual and Seasonal Changes in Offspring Sex Ratio in a Bat. PLoS ONE 7(5): e36344. doi:10.1371/journal.pone.0036344http://www.plosone.org/article/info:doi/10.1371/journal.pone.0036344

QWhat is this about?

What are taken out and what are thrown away?

Figure 2. Correlation between age of females and parturition date.

Barclay RMR (2012) Variable Variation: Annual and Seasonal Changes in Offspring Sex Ratio in a Bat. PLoS ONE 7(5): e36344. doi:10.1371/journal.pone.0036344http://www.plosone.org/article/info:doi/10.1371/journal.pone.0036344

Figure 1. Seasonal variation in offspring sex ratio.

Barclay RMR (2012) Variable Variation: Annual and Seasonal Changes in Offspring Sex Ratio in a Bat. PLoS ONE 7(5): e36344. doi:10.1371/journal.pone.0036344http://www.plosone.org/article/info:doi/10.1371/journal.pone.0036344

Figure 1. Seasonal variation in offspring sex ratio.

Barclay RMR (2012) Variable Variation: Annual and Seasonal Changes in Offspring Sex Ratio in a Bat. PLoS ONE 7(5): e36344. doi:10.1371/journal.pone.0036344http://www.plosone.org/article/info:doi/10.1371/journal.pone.0036344

QWhat is this about?

What are taken out and what are thrown away?

Figure 1. Seasonal variation in offspring sex ratio.

Barclay RMR (2012) Variable Variation: Annual and Seasonal Changes in Offspring Sex Ratio in a Bat. PLoS ONE 7(5): e36344. doi:10.1371/journal.pone.0036344http://www.plosone.org/article/info:doi/10.1371/journal.pone.0036344

5′- and 3′-end distributions (TSB). 5′ and 3′ ends within the limits of recessing <300 nt and protruding <1,000 nt from their corresponding annotated ORFs were plotted as histograms.

Høvik H et al. J. Bacteriol. 2012;194:100-114

5′- and 3′-end distributions (TSB). 5′ and 3′ ends within the limits of recessing <300 nt and protruding <1,000 nt from their corresponding annotated ORFs were plotted as histograms.

Høvik H et al. J. Bacteriol. 2012;194:100-114

QWhat is this about?

What are taken out and what are thrown away?

5′- and 3′-end distributions (TSB). 5′ and 3′ ends within the limits of recessing <300 nt and protruding <1,000 nt from their corresponding annotated ORFs were plotted as histograms.

Høvik H et al. J. Bacteriol. 2012;194:100-114

Figure 4. Scatter plot of age versus biomarker summary score for men and women from the Estonian Biobank cohort.

Fischer K, Kettunen J, Würtz P, Haller T, et al. (2014) Biomarker Profiling by Nuclear Magnetic Resonance Spectroscopy for the Prediction of All-Cause Mortality: An Observational Study of 17,345 Persons. PLoS Med 11(2): e1001606. doi:10.1371/journal.pmed.1001606http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001606

Figure 4. Scatter plot of age versus biomarker summary score for men and women from the Estonian Biobank cohort.

Fischer K, Kettunen J, Würtz P, Haller T, et al. (2014) Biomarker Profiling by Nuclear Magnetic Resonance Spectroscopy for the Prediction of All-Cause Mortality: An Observational Study of 17,345 Persons. PLoS Med 11(2): e1001606. doi:10.1371/journal.pmed.1001606http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001606

QWhat is this about?

What are taken out and what are thrown away?

Figure 4. Scatter plot of age versus biomarker summary score for men and women from the Estonian Biobank cohort.

Fischer K, Kettunen J, Würtz P, Haller T, et al. (2014) Biomarker Profiling by Nuclear Magnetic Resonance Spectroscopy for the Prediction of All-Cause Mortality: An Observational Study of 17,345 Persons. PLoS Med 11(2): e1001606. doi:10.1371/journal.pmed.1001606http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001606

Figure 5. Cumulative probability of death in the Estonian Biobank cohort by percentiles of the biomarker summary score.

Fischer K, Kettunen J, Würtz P, Haller T, et al. (2014) Biomarker Profiling by Nuclear Magnetic Resonance Spectroscopy for the Prediction of All-Cause Mortality: An Observational Study of 17,345 Persons. PLoS Med 11(2): e1001606. doi:10.1371/journal.pmed.1001606http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001606

Figure 6. Discrimination curves for 5-y mortality in FINRISK cohort.

Fischer K, Kettunen J, Würtz P, Haller T, et al. (2014) Biomarker Profiling by Nuclear Magnetic Resonance Spectroscopy for the Prediction of All-Cause Mortality: An Observational Study of 17,345 Persons. PLoS Med 11(2): e1001606. doi:10.1371/journal.pmed.1001606http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001606

Figure 6. Discrimination curves for 5-y mortality in FINRISK cohort.

Fischer K, Kettunen J, Würtz P, Haller T, et al. (2014) Biomarker Profiling by Nuclear Magnetic Resonance Spectroscopy for the Prediction of All-Cause Mortality: An Observational Study of 17,345 Persons. PLoS Med 11(2): e1001606. doi:10.1371/journal.pmed.1001606http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001606

QWhat is this about?

What are taken out and what are thrown away?

Figure 6. Discrimination curves for 5-y mortality in FINRISK cohort.

Fischer K, Kettunen J, Würtz P, Haller T, et al. (2014) Biomarker Profiling by Nuclear Magnetic Resonance Spectroscopy for the Prediction of All-Cause Mortality: An Observational Study of 17,345 Persons. PLoS Med 11(2): e1001606. doi:10.1371/journal.pmed.1001606http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001606

Figure 1. Odds ratio of death for transfusion compared to no transfusion by risk category.

Perel P, Clayton T, Altman DG, Croft P, et al. (2014) Red Blood Cell Transfusion and Mortality in Trauma Patients: Risk-Stratified Analysis of an Observational Study. PLoS Med 11(6): e1001664. doi:10.1371/journal.pmed.1001664http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001664

Figure 1. Odds ratio of death for transfusion compared to no transfusion by risk category.

Perel P, Clayton T, Altman DG, Croft P, et al. (2014) Red Blood Cell Transfusion and Mortality in Trauma Patients: Risk-Stratified Analysis of an Observational Study. PLoS Med 11(6): e1001664. doi:10.1371/journal.pmed.1001664http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001664

QWhat is this about?

What are taken out and what are thrown away?

Figure 1. Odds ratio of death for transfusion compared to no transfusion by risk category.

Perel P, Clayton T, Altman DG, Croft P, et al. (2014) Red Blood Cell Transfusion and Mortality in Trauma Patients: Risk-Stratified Analysis of an Observational Study. PLoS Med 11(6): e1001664. doi:10.1371/journal.pmed.1001664http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001664

Figure 3. Time courses of RT-related activation in representative gray matter ROIs.

Yarkoni T, Barch DM, Gray JR, Conturo TE, et al. (2009) BOLD Correlates of Trial-by-Trial Reaction Time Variability in Gray and White Matter: A Multi-Study fMRI Analysis. PLoS ONE 4(1): e4257. doi:10.1371/journal.pone.0004257http://www.plosone.org/article/info:doi/10.1371/journal.pone.0004257

Figure 3. Time courses of RT-related activation in representative gray matter ROIs.

Yarkoni T, Barch DM, Gray JR, Conturo TE, et al. (2009) BOLD Correlates of Trial-by-Trial Reaction Time Variability in Gray and White Matter: A Multi-Study fMRI Analysis. PLoS ONE 4(1): e4257. doi:10.1371/journal.pone.0004257http://www.plosone.org/article/info:doi/10.1371/journal.pone.0004257

Q7What is this about?

What are taken out and what are thrown away?

Figure 3. Time courses of RT-related activation in representative gray matter ROIs.

Yarkoni T, Barch DM, Gray JR, Conturo TE, et al. (2009) BOLD Correlates of Trial-by-Trial Reaction Time Variability in Gray and White Matter: A Multi-Study fMRI Analysis. PLoS ONE 4(1): e4257. doi:10.1371/journal.pone.0004257http://www.plosone.org/article/info:doi/10.1371/journal.pone.0004257

Figure 1. Network Illustrating Structural Parameters.

Christakis NA, Fowler JH (2010) Social Network Sensors for Early Detection of Contagious Outbreaks. PLoS ONE 5(9): e12948. doi:10.1371/journal.pone.0012948http://www.plosone.org/article/info:doi/10.1371/journal.pone.0012948

Figure 1. Network Illustrating Structural Parameters.

Christakis NA, Fowler JH (2010) Social Network Sensors for Early Detection of Contagious Outbreaks. PLoS ONE 5(9): e12948. doi:10.1371/journal.pone.0012948http://www.plosone.org/article/info:doi/10.1371/journal.pone.0012948

Q8What is this about?

What are taken out and what are thrown away?

Figure 1. Network Illustrating Structural Parameters.

Christakis NA, Fowler JH (2010) Social Network Sensors for Early Detection of Contagious Outbreaks. PLoS ONE 5(9): e12948. doi:10.1371/journal.pone.0012948http://www.plosone.org/article/info:doi/10.1371/journal.pone.0012948

Figure 3. Empirical differences in flu contagion between “friend” group and randomly chosen individuals.

Christakis NA, Fowler JH (2010) Social Network Sensors for Early Detection of Contagious Outbreaks. PLoS ONE 5(9): e12948. doi:10.1371/journal.pone.0012948http://www.plosone.org/article/info:doi/10.1371/journal.pone.0012948

Figure 3. Empirical differences in flu contagion between “friend” group and randomly chosen individuals.

Christakis NA, Fowler JH (2010) Social Network Sensors for Early Detection of Contagious Outbreaks. PLoS ONE 5(9): e12948. doi:10.1371/journal.pone.0012948http://www.plosone.org/article/info:doi/10.1371/journal.pone.0012948

Q9What is this about?

What are taken out and what are thrown away?

Figure 3. Empirical differences in flu contagion between “friend” group and randomly chosen individuals.

Christakis NA, Fowler JH (2010) Social Network Sensors for Early Detection of Contagious Outbreaks. PLoS ONE 5(9): e12948. doi:10.1371/journal.pone.0012948http://www.plosone.org/article/info:doi/10.1371/journal.pone.0012948

Circular transcriptome map showing the normalized RNAseq transcription signals derived from the MIN-cultured cells.

Høvik H et al. J. Bacteriol. 2012;194:100-114

Circular transcriptome map showing the normalized RNAseq transcription signals derived from the MIN-cultured cells.

Høvik H et al. J. Bacteriol. 2012;194:100-114

QWhat is this about?

How do you summarize these?

Circular transcriptome map showing the normalized RNAseq transcription signals derived from the MIN-cultured cells.

Høvik H et al. J. Bacteriol. 2012;194:100-114

Figure 4. Progression of flu contagion in the friendship network over time.

Christakis NA, Fowler JH (2010) Social Network Sensors for Early Detection of Contagious Outbreaks. PLoS ONE 5(9): e12948. doi:10.1371/journal.pone.0012948http://www.plosone.org/article/info:doi/10.1371/journal.pone.0012948

Figure 4. Progression of flu contagion in the friendship network over time.

Christakis NA, Fowler JH (2010) Social Network Sensors for Early Detection of Contagious Outbreaks. PLoS ONE 5(9): e12948. doi:10.1371/journal.pone.0012948http://www.plosone.org/article/info:doi/10.1371/journal.pone.0012948

QWhat is this about?

How do you summarize these?

Figure 4. Progression of flu contagion in the friendship network over time.

Christakis NA, Fowler JH (2010) Social Network Sensors for Early Detection of Contagious Outbreaks. PLoS ONE 5(9): e12948. doi:10.1371/journal.pone.0012948http://www.plosone.org/article/info:doi/10.1371/journal.pone.0012948

QWhat is this about?

What are taken out and what are thrown away?

QWhat is this about?

How do you summarize these?