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Powermarker及TASSEL软件使用操作纪要(转载)  

2011-11-04 17:04:56|  分类: GWAS |  标签: |举报 |字号 订阅

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      声明:以下内容来自 文子的关联分析BLOGhttp://blog.sina.com.cn/s/blog_4b55f4130100n1zg.html)。强力推荐,希望对大家有用!顺便小小提示下,文子为本人师兄,呵呵!

Part 1Genetic diversity and cluster analysis case analysis

Related Software:Powermarker V3.25;Figtree

Case used Data :169clDiliPowerMarker

Key steps:

1. 右击”dataset”后, 左击弹出的“import”,左击“Browse”选择数据文件所在文件夹。

2.Column Delimeters(列定义项)选项里选中“Space”,点击“next”。

3.Column列中line和group的类型改为“categorical”,操作方法为左击line后,左击Categorical, 左击group后,左击Categorical. 注意右侧Hierarchy框中,level-1下拉框选择“line”,level-2下拉框选择“group”,点击“next”及随后的“finish”至数据录入成功。

4.点击窗口顶部“Analysis”,在phylogene后拉框中选择compute frequence,在弹出的对话框中点击数据文件名“169clDiliPowerMarker”后,注意选择右侧相应的计算水平level-1,点击submit.

5. 点击窗口顶部“Analysis”,在Phylogene后拉框中选择“Frequence Based Distance”,在弹出的对话框中点击数据文件名“169clDiliPowerMarker.frequency”后,注意选择右侧距离计算方法,最后点击submit。

6. 点击窗口顶部“Analysis”,在phylogene后拉框中选择“UPGMA/ NJ tree”,在弹出的对话框中点击数据文件名“169clDiliPowerMarker.frequency.share allele”后,注意选择右侧聚类模型,最后点击submit。

7. 点击窗口顶部“Data”,选择Batch export, 弹出的对话框中点击以NJ或upgma结尾的数据文件名,选择输出文件保存路径,再点击submit.

8.用Figtree软件打开输出树形图文件进行编辑。

 

Part2 Association mapping Case Studies

By using the data files in the tutorial dataset, we create following cases to illustrate the usage of

association study performed by GLM and MLM.

Case Data type

1 Phenotype + Candidate SNP markers (haploid)

2 Phenotype + Candidate SNP markers (haploid) + Q

3 Phenotype + Candidate SNP markers (haploid) + Q + K

4 Phenotype + SSR markers (haploid)

5 Phenotype + Candidate SNP markers (diploid)

In practice, the association study may involve the combination of two or more cases listed above.. For

example, diploid SSR markers is equivalent to Case 5 + 6.

 Case 1: Phenotype + Candidate SNP markers (haploid)

This is the simplest association analyses with assumption with completely random mating population.

Files used

1) d8coding_rn_rename_sel.txt

2) three_traits_rn_rename.txt

Statistical model: y = marker + e

Key steps

1. Join the two files by highlight them and then click “AND” Joint button on data Panel.

2. Highlight the joint file and click GLM on Analysis panel. Click OK on the Dada definition dialog

window and click RUN button on “Build a Linear Model” dialog window.

Results

The result is display as “GLM_three_traits_rn_rename + d8coding_rn_rename_sel” on data tree.

The result was also saved in the result folder in the tutorial dataset.

 Case 2: Phenotype + Candidate SNP markers (haploid) + Q

Thin case introduce population structure (Q) to reduce false positives due to population stratification.

Files used

1) d8coding_rn_rename_sel.txt

2) three_traits_rn_rename.txt

3) popStructure_taxa286_rn_rename.txt.

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Statistical model: y = marker + Q + e

Key steps

1. Join the three files by highlight them and then click “AND” Joint button on data Panel.

2. Highlight the joint file and click GLM on Analysis panel. Change Q1 and Q2 as Covariate and

exclude Q3 on the Dada definition dialog window , click OK to go to “Build a Linear Model”

dialog window and click RUN button.

Results

The result is display as “GLM_d8coding_rn_rename_sel + three_traits_rn_rename +

popStructure_taxa286_rn_rename” on data tree.

 Case 3: Phenotype + Candidate SNP markers (haploid) + Q +K

Thin case use mixed model approach to incorporate both population structure (Q) and kinship among

individuals to reduce false positives due to population stratification and relatedness at individual level.

Files used

1) d8coding_rn_rename_sel.txt

2) three_traits_rn_rename.txt

3) popStructure_taxa286_rn_rename.txt.

4) kinship_277taxa_by_Spagedi_rn_sq_rename.txt.

Statistical model: y = marker + Q + K + e

Key steps

1. Join the top three files by highlight them and then click “AND” Joint button on data Panel. Note:

Do not join the kinship file.

2. Highlight the joint file and the kinship file, click MLM on Analysis panel. Change Q1 and Q2 as

Covariate and exclude Q3 on the Dada definition dialog window , click OK to go to “Build a

Mixed Linear Model” dialog window . Click “>>” button to add all factors. and click Next button.

3. Modify heritability of dpoll to 0.45, choose the option of “Use the heritability given above” and

change analysis method to “EM”. Click Run.

Results

The result is display as “MLM_Asso_d8coding_rn_rename_sel + three_traits_rn_rename +

popStructure_taxa286_rn_rename” on data tree.

Case 4: Phenotype + Candidate SSR markers (haploid)

This case introduces usage of SSR markers which need to be converted first.

Files used

1) haploid_SSR_A

2) diploid_Stru

3) diploid_traits.

Statistical model: y = marker + Q + e

Key steps

1. Currently the Joint function does not work with directly loaded SSR polymorphism markers such

as SSR. They need to be converted first. highlight the SSR data set and click Genotype on data

81

panel. Then choose the “Convert into one gametic alignment. A data called “Haplotype” is added

to data tree.

2. Highlight dataset Haplotype, diploid_traits and diploid_Stru, then click “AND” Joint button on

data Panel.

3. Highlight the joint file and click GLM on Analysis panel. Change PC1, PC2 and PC2 as

Covariate on the Dada definition dialog window , click OK to go to “Build a Linear Model”

dialog window and click RUN button.

Results

The result is display as “GLM_Haplotype + diploid_traits + diploid_Stru” on data tree.

Case 5: Phenotype + Candidate SNP markers (diploid)

Multiple ploid genetic markers have to be converted to genotype indicated by single character, which can

be performed by the function of Genotype in data panel.

Files used

1) diploid_SNP

2) diploid_Stru

3) diploid_traits.

Statistical model: y = marker + Q + e

Key steps

1. Highlight the diploid SNP marker data set and click Genotype on data panel. Then choose the

option “Create alignment based on genotypic status (eg. A:a>Aa)”. A data called “GenoStates” is

added to data tree.

2. Highlight dataset GenoStates, diploid_traits and diploid_Stru, then click “AND” Joint button on

data Panel.

3. Highlight the joint file and click GLM on Analysis panel. Change PC1, PC2 and PC2 as

Covariate on the Dada definition dialog window, click OK to go to “Build a Linear Model” dialog

window and click RUN button.

Results

The result is display as “GLM_diploid_traits + diploid_Stru + GenoStates” on data tree.

Part 3 Genetic linkage map construction Case Study

Key steps:

1> prepare data N1231.txt;2>photo 1231.out;3> cent kos;4> s all;5> group;6> s {2 3 4 5 … };7> s 2 4 5; 8 > try ; 9>map


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