Statistical Genetics 統計遺伝学

Presentation on theme: "Statistical Genetics 統計遺伝学"— Presentation transcript:

1 Statistical Genetics 統計遺伝学
2010/05/21 Ryo Yamada Unit of Statistical Genetics Center for Genomic Medicine Graduate School of Medicine Kyoto University

2 太陽 おけら てのひら みみにみみず あめんぼ みつばち とんぼ かえる 私が両手をひろげても、 お空はちっとも飛べないが、
　　　私が両手をひろげても、 　　　お空はちっとも飛べないが、 　　　飛べる小鳥は私のやうに、 　　　地面（じべた）を速くは走れない。 　　　私がからだをゆすっても、 　　　きれいな音は出ないけど、 　　　あの鳴る鈴は私のやうに、 　　　たくさんな唄は知らないよ。 　　　鈴と、小鳥と、それから私、 　　　みんなちがって、みんないい。 みつばち とんぼ かえる 2

3 瓜二つ 瓜の蔓に茄子はならぬ 鳶が鷹を生む カエルの子はカエル 3

4 What to study? How to study?
What do you want to know? How do you want to know it?

5 Genetics Genotype Phenotype

6 Genetics Genotype Phenotype Identity Variation
How to grab “Genotype” and “Phenotype” with their “Identity” and “Variation”. One way is to make a catalogue of facts among “them”. The other way is to give a strategy to make the catalogue.

7 Sexual and Asexual Reproduction Graph

8 RNA codon table

9 RNA codon table can be drawn as a tree.

10 What is the distribution of length of chromosomes like?

11 Complementary strand, for what?

12 Cross-overs and recombinatios

13 What is the relation between crossovers and identity of origin?

14 What is the distribution of segment-length between crossovers?
Exponential...

15 Some chromosomes leave many copies but others none.

16 Variants will drift out from the world.

17 Variants will drift out from the world.

18 Alleles and haplotypes and their relation.

19 Genotype Phenotype Intermediate phenotype Terminal phenotype

20 Categorical data and sets.
カテゴリ型データと集合

21 Ordered and Non-ordered.

22 High-dimensional data and graph

23 Phylogety, a tree

24 Distance is a way to quantitate relation.
Three items that make a triangle can be connected as a star without changing their pathway-distance.

25 Distance: More than one definition

26 Items can be expressed as a tree when distance among them are given.
Different “distances” give different trees.

27 Quantitative data and a tree
S S S S S

28 Number line is a tree. Relations among items are very simple.

29 When not too simple, the relation takes a tree.
Root, leaves. Ideas in graph give us ideas how to treat data.

30 Same or different as a tree?

31 A tree in classical biology

32 Heatmap Data-mining approach also uses trees.

33 Tree needs “distance” with its definition.
Clustering methods also need definition to make tree structure..

34 Data give trees and change the order in items.
When the order in items are not changed and when relation among the items are displayed, it is correlation matrix.

35 Relations among columns
Original data Relations among lines Relations among columns and lines

36 Trees in classical genetics: Pedigrees

37

38 Relation between humans. Relation between chromosomes.

39 A human relation can be multiple chromosomal relations.

40 Chromosomes have two parental chromosomes.
But a base has only one parental base.

41 Chromosomal relations in generations.

42 Graphs are being used for biology

43 Graphs for individuals. Distributions for populations.

44

45 Population. Chronological changes.

46 Populations in “Space” and “Time”.
Finite space vs. Infinite Space

47 Models how to handle space and time.
Equilibrium. Steady state.

48 疾患原因・薬剤応答性遺伝因子探索 GWAS

49 ? ? ? ? ? ? DNA配列 次世代 シークエンス eQTL GWAS E1 E2 E3 E4 E5 D1 D1a D2 D1b
エピゲノム修飾 ? 次世代 シークエンス eQTL ? ネットワーク (転写物・翻訳物) ? ? ? GWAS ? E1 E2 E3 E4 E5 疾患に共通する因子 D1 疾患とその亜分類 D1a D2 D1b D2b D3 D2a D2c D4 D5

50 ? in Statistical genetics?
Welcome Any questions on how to handle bio-medical data ? Also welcome Ryo Yamada, M.D., Ph.D. Unit of Statisical Genetics 4F Kaibou-center building phone: (+81) fax: (+81) 統計遺伝学分野 山田　亮 医学部解剖センター棟４階