phenotype data for GWAS

[Ruijuan li]

Dear all,

I am working on a project to find the SNPs associated with nematode resistance of cotton. Now I have the genotype data from GBS, I also have the original phenotype data (nematode count relative to susceptible control). Different results (i.e. significant associated SNPs) were generated if I use the original phenotype data and rank-based transformed data (e.g. 1-10 rated as 1, 11-30 rated as 2, 31-60 rated as 3, and >60 rated as 4). Attached are the two Manhattan plots I got with two forms of phenotype data: 1 got from original phenotype data, 2 from rank-based transformed data. 

My question is which phenotype data format get more reliable result from GWAS? the original phenotype data or the rank-based transformed data? should I validate the result by using R?  

[Edward S. Buckler]

Most of the statistic assume normally distributed data.  I would assume that you have some outliers and small datasets.  I would transform data and/or evaluate the outliers.

Cheers-

Ed

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[Ruijuan li]

Dr. Buckler,

I used a filtered set of over 8,000 SNPs for 249 samples with phenotype data (thought this is a reasonable sample size). I understand to transform my data to get a normal distribution, but how to evaluate the outliner? Below is the frequency distribution of my original phenotype data. 

On Thursday, September 17, 2015 at 4:05:08 PM UTC-5, Edward Buckler wrote:

Most of the statistic assume normally distributed data.  I would assume that you have some outliers and small datasets.  I would transform data and/or evaluate the outliers.

Cheers-

Ed

On Sep 17, 2015, at 3:19 PM, Ruijuan li <rzl...@gmail.com> wrote:

Dear all,

I am working on a project to find the SNPs associated with nematode resistance of cotton. Now I have the genotype data from GBS, I also have the original phenotype data (nematode count relative to susceptible control). Different results (i.e. significant associated SNPs) were generated if I use the original phenotype data and rank-based transformed data (e.g. 1-10 rated as 1, 11-30 rated as 2, 31-60 rated as 3, and >60 rated as 4). Attached are the two Manhattan plots I got with two forms of phenotype data: 1 got from original phenotype data, 2 from rank-based transformed data. 

My question is which phenotype data format get more reliable result from GWAS? the original phenotype data or the rank-based transformed data? should I validate the result by using R?  

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